GREAT LAKES ECOSYSTEM INDICATOR PROJECT REPORT Indicators -Final.pdf · ecosystem indicators to gauge progress under the Great Lakes Water Quality Agreement. The work on ecosystem

GREAT LAKES ECOSYSTEM

INDICATOR PROJECT REPORT

A Report of the IJC Priority Assessment of Progress towards Restoring the Great Lakes

June 2014

INTERNATIONAL JOINT COMMISSION Canada and United States

COMMISSION MIXTE INTERNATIONALE Canada et États-Unis

(inside front cover)

For More Information

For more information please visit the IJC’s website: www.ijc.org.

Information also can be obtained by contacting any of the following IJC offices:

United States Section Office 2000 L Street, NW Suite 615 Washington, DC 20440 Phone: 202-736-9000 Fax: 202-632-2006

Canadian Section Office 234 Laurier Avenue West 22nd Floor Ottawa, ON K1P 6K6 Phone: 613-995-2984 Fax: 613-993-5583

Great Lakes Regional Office 100 Ouellette Avenue 8th Floor Windsor, ON N9A 6T3 Phone: 519-257-6700 Fax: 519-257-6740

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ACKNOWLEDGEMENTS This report on ecosystem indicators is the product of a binational cooperative effort that

involved over 100 experts from Canada and the United States. The International Joint

Commission expresses its sincere appreciation to the many scientific experts from

multiple government, academic, non-profit, and other organizations who contributed to

this report. Their collaborative efforts provide the foundation for the Commission to

recommend to the governments of Canada and the United States measures to effectively

assess progress towards achieving the promise of the Great Lakes Water Quality

Agreement. The workgroup’s efforts will inform how the Commission will

independently assess progress under the Agreement.

Contributing experts are listed in each indicator report. We note, however, that the

findings and recommendations in this report are solely the responsibility of the

Commission.

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EXECUTIVE SUMMARY The Great Lakes Water Quality Agreement charges the International Joint Commission (the

Commission) with the responsibility for assessing and reporting upon the progress of the

governments of Canada and the United States in their implementation of the Agreement. To

meet this charge, the Commission established a three year priority (2012-2015) to develop

approaches and tools for undertaking the assessment. This Commission report on ecosystem

indicators is a synthesis of extensive scientific analysis and provides additional technical analysis

building upon the work and recommendations of IJC’s binational workgroup reports issued in

2013 titled: Great Lakes Ecosystem Indicators Summary Report: the Few That Tell Us the Most

and Technical Report on Ecosystem Indicators.

The overall objective of the Assessment of Progress priority is to ensure that the Commission is

well placed to fulfill its assessment and reporting responsibilities assigned by the Great Lakes

Water Quality Agreement. The Commission believes that an assessment of progress under the

Agreement should include the measurement and reporting of quantifiable indicators related to

Agreement objectives. Scientifically sound indicators applied consistently over time are

essential to track changes in Great Lakes water quality.

Identifying key ecosystem indicators that tell us the most about the Great Lakes is the first

project under the Assessment of Progress priority. Targeted ecosystem indicators are important

tools to inform the critical decisions for Great Lakes protection and restoration efforts to benefit

the millions of people who depend on and enjoy the waters of the Great Lakes.

The Commission recommends 16 indicators composed of 41 measures to be the best indicators

for assessing progress for the ecosystem under the new Agreement. The suite of 16 ecosystem

indicators are the “few that tell us the most” and this report defines and discusses their relevance

to Agreement objectives and ecosystem health conditions, their constituent measures and how

the indicators should be interpreted. The ecosystem indicators provide good coverage of the

Agreement Objectives and Annexes with the smallest number of indicators possible. Key gaps

in the coverage, including indicators for human health and program effectiveness, will be

addressed through separate projects also being conducted under the Commission’s Assessment

of Progress Priority.

The Commission recommends that the governments of Canada and the United States consider

using the Commission’s recommended ecosystem indicators in State of the Lakes Ecosystem

Conference (SOLEC) reporting. As part of this process, the Commission also recommends that

the governments review the indicators with respect to how easily they can be fully implemented

and provide feedback to the Commission regarding their potential for operationalization.

A comparison of the Commission’s ecosystem indicators and ecosystem indicators in the recent

SOLEC report by the governments is also included in this report as an initial step in that

assessment process. While the Commission did find some overlap; 23 out of the 41 measures of

IJC ecosystem indicators are defined differently from SOLEC indicators.

The next steps for the Commission’s Assessment of Progress Priority are to examine how best to

use the indicators in this report for reporting on progress, raising awareness and encouraging

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action – the tasks key to the Commission’s responsibilities under the Agreement. The

Commission is also considering identifying a small set of apex indicators to guide Commission

assessment and reporting activities and for communication with the public. Feedback from the

governments regarding the operationalization of the recommended indicators will be important

input as the Commission continues its work to develop tools and approaches to effectively assess

progress of achieving the objectives of the Great Lakes Water Quality Agreement.

The Commission thanks the SOLEC representatives involved for their constructive engagement

in the Commission’s work on indicators to date. The Commission looks forward to further

constructive engagement with the governments as the Assessment of Progress Priority work

moves toward completion in 2015.

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TABLE OF CONTENTS

ACKNOWLEDGEMENTS ........................................................................................................ 1

EXECUTIVE SUMMARY .......................................................................................................... 2

TABLE OF CONTENTS............................................................................................................. 4

CHAPTER 1: INTRODUCTION .............................................................................................. 6

1.1 Purpose of the Report ........................................................................................................... 6

1.2 Establishment of the Assessment of Progress Priority .................................................. 6

1.3 Background to the Report.................................................................................................... 7

1.4 Organization of the Report ................................................................................................. 9

CHAPTER 2: INDICATOR DEVELOPMENT PROCESS ................................................ 10

CHAPTER 3: DESCRIPTIONS OF ECOSYSTEM INDICATORS ................................. 11

3.1 Introduction ......................................................................................................................... 11

3.2 Physical Indicators .............................................................................................................. 12

3.2.1 Coastal Habitat – Shoreline Alteration Index .......................................................................................... 12

3.2.2 Extent, Composition, and Quality of Coastal Wetlands ........................................................................ 14

3.2.3 Land Cover and Fragmentation Status..................................................................................................... 17

3.2.4 Seasonal and Long-Term Fluctuations in Great Lakes Water Levels ................................................... 19

3.2.5 Tributary Physical Integrity ....................................................................................................................... 22

3.2.6 Water Temperature ..................................................................................................................................... 26

3.3 Chemical Indicators ............................................................................................................ 28

3.3.1 Atmospheric Deposition of Chemicals of Mutual Concern ................................................................... 28

3.3.2 Chemicals of Mutual Concern in Water ................................................................................................... 29

3.3.3 Contaminants in Groundwater ................................................................................................................. 31

3.3.4 Persistent, Bioaccumulating, Toxic (PBT) in Biota .................................................................................. 34

3.3.5 Phosphorus Loads and In-Lake Concentrations ..................................................................................... 36

3.4 Biological Indicators ........................................................................................................... 37

3.4.1 Aquatic Invasive Species: Invasion Rates and Impacts .......................................................................... 37

3.4.2 Abundance and Distribution of Fish-Eating and Colonial Nesting Birds ........................................... 39

3.4.3 Lower Food Web Productivity and Health .............................................................................................. 41

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3.4.4 Fish Species of Interest ................................................................................................................................ 44

3.4.5 Harmful and Nuisance Algae .................................................................................................................... 46

CHAPTER 4: ECOSYSTEM INDICATOR RELEVANCE TO THE AGREEMENT

OBJECTIVES AND A COMPARISON WITH SOLEC INDICATORS ......................... 48

4.1 Ecosystem Indicator Relevance to the Agreement Objectives ................................... 48

4.2 Comparison of Commission Ecosystem Indicators and SOLEC Indicators ............ 51

CHAPTER 5: DISCUSSION AND RECOMMENDATIONS .......................................... 55

5.1 The Ecosystem Indicators .................................................................................................. 55

5.2 State of the Great Lakes 2011 reporting by SOLEC ...................................................... 55

5.3 Next Steps for the Commission ........................................................................................ 56

5.4 Reporting on the Assessment of Progress Priority ....................................................... 56

REFERENCES ............................................................................................................................ 58

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Chapter 1: INTRODUCTION

1.1 Purpose of the Report

The purpose of this report is to present the Commission’s work done to date on the first project

of the Assessment of Progress priority. This report on ecosystem indicators from the

Commission provides additional analysis and technical information and is intended to build upon

the Commission Workgroup reports issued in June 2013: Great Lakes Ecosystem Indicators

Summary Report: the Few That Tell Us the Most and Technical Report on Ecosystem Indicators

(http://www.ijc.org/en_/AOP/Publications).

The report includes recommendations to the governments of Canada and the United States with

respect to the ecosystem data they are collecting and providing to the Commission, and to the

general public. Recommendations are aimed at facilitating the work of the Commission in

assessing the progress of the governments of Canada and the United States in their

implementation of the Great Lakes Water Quality Agreement (the Agreement) and increasing

public awareness of the quality of the Waters.

Recommendations relate to the adoption and monitoring of a set of ecosystem indicators that are

considered to be the key indicators in assessing the governments’ progress in achieving the

General and Specific Objectives of the Agreement. The report sets out the details of these

recommended indicators, along with the binational process for their identification and

development.

The report also aims to set this work on ecosystems indicators in the context of the

Commission’s Assessment of Progress Priority giving background and next steps for this area of

work.

Although this report was prepared to provide advice to the governments of Canada and the

United States regarding the collection and reporting of monitoring data for the Great Lakes. The

findings and recommendations of the report will also be of interest to a broad audience of

agencies, water users, residents, organizations and decision-makers concerned about water

quality and the implementation of the Agreement.

1.2 Establishment of the Assessment of Progress Priority

In 2012, the Commission established the development of approaches and tools for the assessment

of progress under the 2012 Great Lakes Water Quality Agreement as one of its Great Lakes

priorities covering the 2012-2015 triennial cycle. The overall objective of the Assessment of

Progress priority is to ensure that the Commission is well placed to fulfill its mandate under the

Agreement to report to the Parties and to the State and Provincial Governments concerning

progress toward the achievement of the General and Specific Objectives, including, as

appropriate, matters related to Annexes to the Agreement.

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The Commission believes that an assessment of progress under the Agreement should include

the measurement and reporting of quantifiable indicators related to Agreement objectives.

This Commission report is the first issued under the Assessment of Progress Priority and it

focuses on the key ecosystem indicators best suited to assess progress towards meeting the goals

and objectives of the Great Lakes Water Quality Agreement. The Commission has spent much

of the past two years developing a list of ecosystem indicators that can be termed as “the few that

tell us the most”. This report presents the outcome of the work to identify and define the best

ecosystem indicators to gauge progress under the Great Lakes Water Quality Agreement.

The work on ecosystem indicators is only one aspect of this priority. Separate projects are on-

going with respect to human health indicators and program effectiveness indicators. An ultimate

aim of the priority is to combine these initiatives and, from them, recommend to the governments

of Canada and the United States a smaller apex set of indicators for public communication.

Work conducted under this priority is intended to complement the SOLEC process, by providing

binational advice regarding the development, design and reporting on selected indicators,

including their monitoring needs.

1.3 Background to the Report

The Commission is an independent binational organization created by Canada and the United

States under the Boundary Waters Treaty of 1909. Under the Treaty, the two countries cooperate

to prevent and resolve disputes relating to the use and quality of the many lakes and rivers along

their shared border.

Canada and the United States have been working together closely for over 40 years to manage

and protect the Great Lakes. The two countries committed in the Great Lakes Water Quality

Agreement to restore and protect the physical, chemical, and biological integrity of the waters of

the Great Lakes basin ecosystem. The Governments, private sector, and public have invested

billions of dollars in pollution controls, restoration, and conservation work since the Agreement

was signed in 1972 and significant improvements have been accomplished. However, there are

many continuing concerns and questions about how the lakes are doing, whether we really are

making progress and, if so, how much.

At the request of both governments, under the Great Lakes Water Quality Agreement, the

Commission has a role in advising the two countries on restoration and maintenance of the

chemical, physical, and biological integrity of the waters of the Great Lakes. Most notably in the

context of this report, the Agreement gives the Commission the responsibility of providing to the

governments of Canada and the United States an “Assessment of Progress Report” every three

years. The Assessment of Progress Report is intended to assess the extent to which programs

and other measures are achieving the General and Specific Objectives of the Agreement.

The Commission has had this responsibility to assess and report upon progress made under the

Great Lakes Water Quality Agreement, since the Agreement was revised in 1978 and has issued

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16 biennial reports between 1980 and 2013. The 2012 revised Agreement changed the timing of

the reporting from biennial to triennial.

From 1978 to 1987, the Commission’s biennial assessment of progress reports were produced by

a network of specialized subcommittees that were part of the Commission’s advisory boards.

These boards included government officials who could collect the necessary data to support the

assessment. With the requisite data available, the first four biennial reports were effective at

assessing progress on objectives. However, the 1987 Agreement changed the protocol, the

subcommittees were disassembled, and the responsibility of providing data to the Commission

was transferred to the governments. Then it became a challenge for the Commission to obtain

data that clearly reflected progress towards achieving the objectives of the 1987 Agreement. The

difficulty in obtaining sufficient data led the Commission to change the focus of its biennial

reporting. In 1990, starting with the Fifth Biennial Report, the aim of biennial reporting shifted

and became “not to provide a comprehensive report of all subjects of importance to the Great

Lakes, but rather highlight some issues needing urgent and focused attention” (IJC 1990).

The Commission has drawn attention to the need for comprehensive data from the Parties in the

past. The 13th Biennial Report of Great Lakes Water Quality (IJC 2006a) was devoted to the

challenge of accountability, including the need for the Parties to provide data, to improve

reporting particularly as it related to the achievement of Agreement objectives. The report

advocated a smaller number of SOLEC indicators (relative to the about 80 SOLEC indicators at

that time), such that each indicator retained directly related to the objectives of the Agreement

and was adequately funded.

Scientifically sound indicators applied consistently over time are essential to track changes in

Great Lakes water quality. The Commission has long advocated using indicators to measure

progress toward Agreement objectives and has recommended criteria for selecting them (IJC

1991; IJC 1996; IJC 2000; IJC 2006b). The Commission also recognizes that resources are only

available to monitor, compile, and present information on a limited set of indicators.

Furthermore, conveying clear information to the public and to decision makers is best

accomplished using a small set of scientifically sound indicators communicated in non-technical

language.

In anticipation of the new GLWQA in 2011, the Commission initiated the return to a more

comprehensive assessment of progress for its biennial report. The 16th Biennial Report,

published in 2013, used seven indicators of chemical integrity, five indicators of biological

integrity, two of physical integrity, and two performance indicators to assess progress under the

Agreement since the Agreement was last revised in 1987. The 16 indicators used in the report

were selected by Commission staff based on relevance to GLWQA objectives and availability of

data. While the report was very useful and provided a retrospective analysis over the past 25

years, the amount and type of data available limited the extent of assessment that could be made.

To the Commission it was clear that a set of core indicators related to Agreement objectives and

useful for a concise assessment of progress was needed and that these core indicators should be

consistently monitored over time.

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With the renewal in September 2012 of the Great Lakes Water Quality Agreement, the

Commission seized upon the occasion to reaffirm its commitment to fulfilling its responsibility

under the Agreement of assessing and reporting upon the progress being made toward the

achievement of the General and Specific Objectives of the renewed Agreement, including, as

appropriate, matters related to its Annexes.

SOLEC

The Commission’s work on indicators for assessing the physical, chemical, and biological

integrity of the Great Lakes is reliant upon the excellent work by, and collaboration with, the

State of the Lakes Ecosystem Conference (SOLEC). SOLEC is an initiative by the U.S.

Environmental Protection Agency and Environment Canada on behalf of the two countries. It

involves over 125 scientists and experts from Canada and the U.S. who assemble environmental

information about the Great Lakes ecosystem through the SOLEC process. The conferences are

intended to report on the state of the Great Lakes ecosystem and the major factors impacting it,

and to provide a forum for exchange of this information amongst Great Lakes decision makers.

The conference was held every two years between the first conference in 1994 and the

conference in 2008. Conferences will be held every three years under the 2012 Agreement. The

most recent conference was in 2011. A report on “The State of the Great Lakes” is issued after

each conference.

Through SOLEC, the state of the Great Lakes is assessed using nearly 60 indicators, organized in

a DPSIR (driver, pressure, state, impact, response) framework. The DPSIR framework is an

underlying tool to aid in the selection, organization, and reporting on indicators, which allows

decision makers to understand the linkages between the conditions of the ecosystem, pressures

on the ecosystem, and how human activities are related to the condition of the system. SOLEC

reports are very useful and provided much of the data for the Commission’s 16th Biennial

Report. However, these indicators could be improved for delivering clear and concise messaging

regarding progress in the restoration and maintenance of the Great Lakes. The Commission also

recognizes that prioritizing a core set of indicators could be used to prioritize the limited

resources available for monitoring.

In looking to identify a subset of indicators for assessment and reporting, the Commission

questioned whether the SOLEC ecosystem indicators included the best indicators possible for

making the assessment of progress they desired.

Since the Commission began work on this priority in early 2012, SOLEC has continued to

evolve, in particular in its reporting of the 2011 State of the Lakes Conference. These

developments are discussed in Chapters 4 and 5 of this report.

1.4 Organization of the Report

The rest of this report is organized into the following four chapters and a reference section:

Chapter 2 presents the indicator development process.

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Chapter 3 presents the descriptions for each of the 16 indicators.

Chapter 4 reviews the indicators relevance to the objectives of the GLWQA and the indicators

presented in SOLEC 2011 reporting.

Chapter 5 presents the Commission’s recommendations for the governments with respect to

these ecological indicators as well as the Commission’s own next steps in taking this work

forward under the Assessment of Progress priority.

The report represents a synthesis of extensive scientific analysis. Readers wanting more detailed

information, particularly on the indicator development process, are encouraged to review the

original technical report and summary report prepared by the Work Group as part of the study.

Chapter 2: INDICATOR DEVELOPMENT PROCESS

To meet the objective of identifying a set of key indicators for the assessment of progress in this

priority, an Ecosystem Indicator Work group was formed consisting of members of the

Commission’s Great Lakes Water Quality Board and Great Lakes Science Advisory Board.

SOLEC representatives from Environment Canada and the U.S. Environmental Protection

Agency consulted with the advisory boards in this process and provided assistance and feedback

as the work progressed. Consistent with Commission practices, the indicators were to be

identified through a binational consensus-based process.

The Ecosystem Indicators Work Group developed a work plan that commenced with a literature

search and a review of various national and international programs for assessing ecosystem

health indicators used by the various programs, and criteria used for selection of indicators. The

context and geographic framework for the selection of ecosystem indicators was defined by the

renewed GLWQA. Reviewing and adopting the DPSIR framework, the Work Group decided

that, for the purposes of this project, priority is given to state and possibly impact indicators

which define the physical, chemical, and biological integrity of the Great Lakes ecosystem. This

decision was based on the goal of identifying a small set of indicators to assess progress toward

achieving the Objectives of the Agreement rather than identifying sources of impairments.

Based on the background work, the Work Group agreed upon a set of criteria to be used by an

expert consultation workshop in selecting a set of indicators. The criteria were divided among

four “themes”, including usefulness, data quality, data availability, and practicality. Using these

criteria, there was a bias towards existing indicators with existing data. However, the criteria did

not prevent the identification of new indicators to fill the gaps of existing indicators.

A binational expert consultation workshop was held in Windsor, Ontario, in September 2012.

The workshop was held with the primary objective of establishing a concise list of ecosystem

indicators. Participants at the workshop included various stakeholders, experts on indicator

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development, and scientists with expertise in various disciplines and a diversity of affiliations.

The workshop resulted in a prioritized list of 22 indicators. Through further efforts of the

Ecosystem Indicator Work Group, these 22 indicators were combined into the set of 16

indicators presented in Chapter 3. Each of these indicators has 1-6 measures associated with its

assessment.

The Ecosystem Indicators Work Group then identified experts (1-3 individuals) to draft detailed

descriptions of the indicators and their measures based on input from the participants that

attended the expert consultation workshop. These draft descriptions were subsequently reviewed

by members of the Science Advisory Board, Water Quality Board, as well as the entire group of

workshop participants to ensure alignment with discussions at the meeting. In the summer of

2013, the work-group produced a summary report and a technical report, which are available on

the Commission’s website (www.ijc.org/en_/AOP/Publications). These reports describe in detail

the indicator selection process, their relevance to the GLWQA objectives and annexes, and

provide initial descriptions of the indicators.

After the completion of the reports, the Ecosystem Indicators Work Group felt additional work

was needed to finalize the measures that would be included in each indicator, describe how the

measures would be calculated, and provide adequate information on spatial and temporal

coverage of the measures. Sixteen Indicator Expert Teams (one for each indicator) were

established by Commission staff. The Indicator Teams consisted of the authors of the initial

indicator description, previous Workgroup co-chairs, regional experts of the indicators, and

Commission staff. Each of the indicator teams was charged by the Commission to develop more

details for each indicator to help determine what measures to use, which data are needed, and

how to obtain, synthesize, analyze, and report the findings. Chapter 3 of this report presents the

descriptions of the 16 ecosystem indicators that were refined by the Indicator Teams.

Chapter 3: DESCRIPTIONS OF ECOSYSTEM INDICATORS

3.1 Introduction

This Chapter presents the details of the 16 ecosystem indicators recommended for the

Assessment of Progress under the Great Lakes Water Quality Agreement. It provides

information on (1) the experts involved in the development of each indicator, (2) how each

indicator is defined, (3) relevance of the indicators to Agreement objectives and ecosystem

health conditions, (4) what measures each indicator includes and how each measure should be

calculated, and (5) how the indicators should be interpreted and what caveats and cautions

should be considered when using these indicators. The key measures of each indicator are listed

and described under the heading Descriptions of Measures. The measures under the heading

Other Indicators Considered are those measures that were discussed, but are not recommended to

be used at this time.

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Where the indicators are the same or similar to SOLEC indicators, the experts consulted were

usually also involved in the SOLEC work. This is true for approximately half of the indicators.

The value of these indicators descriptions relative to SOLEC is that the descriptions reinforce the

value of some of the SOLEC indicators, propose useful adjustments to others or propose new

additions to the SOLEC indicator suite. A chart comparing the two indicator sets is presented in

Chapter 4.

The 16 indicators in this Chapter are organized into physical, chemical, and biological groups.

Within each group, the indicators are presented in alphabetical order.

3.2 Physical Indicators

3.2.1 Coastal Habitat – Shoreline Alteration Index

Expert workgroup member: Scudder Mackey

IJC staff: Lizhu Wang

Definition

The indicator uses Shoreline Alteration Index (SAI) as a measure of human modified shoreline

length that is physically and biologically unfavorable to the Great Lakes ecosystems. The

physical and biological components used to calculate the SAI can be measured using

conventional high-resolution aerial photography or satellite imagery at multiple scales. The

physical component is the ratio of lineal length of armored and other “man-made” shoreline

relative to total lineal length of the shoreline. The biological component is the lineal length of

biologically incompatible shoreline structures relative to the total lineal length of human

modified shoreline.

Indicator Relevance

This indicator is directly relevant to GLWQA Annex 7- Habitat and Species. Physical

modifications to the shoreline have disrupted coastal and nearshore processes, flow and littoral

circulatory patterns, altered or eliminated connectivity to coastal wetlands/dunes, and have

altered nearshore and coastal habitat structure.

Description of Measures

SAI is a combination of the ratio of human modified shoreline length to total shoreline length

and the proportion of human modified shoreline length that is biologically compatible (Livchak

and Mackey, 2007).

1. Physical shoreline indicator is the ratio of the lineal length of human modified shoreline

relative to total lineal length of the total shoreline length. More specifically, the P ratio

equals human modified shoreline/total shoreline.

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2. Biological shoreline indicator is the ratio of the lineal length of biologically incompatible

structures (shore perpendicular structures, vertical sheet pile, concrete walls, and other

“man-made” structures that cannot serve as biological habitat) relative to total lineal length

of “man-made” shoreline (B ratio).

3. SAI is calculated by multiplying the physical and biological shoreline indicator values and

subtracting the resulting value from one.

( )

Other Measures Considered

None

Indicator Interpretation and Comments

The value of the physical shoreline measure ranges between 0-1. A value of zero (0) represents a

natural shoreline and a value of one (1) represents a completely human modified shoreline.

The value of the biological shoreline measure ranges between 0-1. A value of zero (0) represents

that the human modified shoreline has no adverse biological or ecological impact, and a value of

one (1) represents 100% of human modified shoreline has significant adverse biological or

ecological impacts.

The value of SAI also ranges from 0-1. A value of zero (0) represents that the shoreline is 100%

biologically or ecologically impacted by shoreline modifications of human activities. A value of

one (1) indicates the shoreline has no biological or ecological impacts even though a portion of

the shoreline may have been modified by human activities.

The greater the SAI value, the more unaltered and biologically compatible the shoreline is. The

SAI is scalable to any shoreline length, and can be applied to present and historical data for

comparison and trend analyses. The advantage of this approach is that as structures are removed

and/or modified to provide habitat enhancements, the indicator will shift toward a more unaltered

or natural state. Conversely, if the number and extent of biologically incompatible shoreline

structures increases, the indicator will shift toward a more altered state. The physical shoreline

indicator, biological shoreline indicator, and SAI can also be used separately. An example of

such narrative descriptions is listed below.

Indicator (Sub) Poor Fair Good Excellent

Physical 0.7 to 1.0 0.4 to 0.7 0.15 to 0.4 0.0 to 0.15

Biological n/a n/a n/a n/a

SAI 0.0 to 0.3 0.3 to 0.6 0.6 to 0.85 0.85o 1.0

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3.2.2 Extent, Composition, and Quality of Coastal Wetlands

Expert workgroup members: Don Uzarski, Dave Ulrich, Denny Albert, Patricia Chow-

Fraser, Matt Cooper, Lucinda Johnson, Kurt Kowalski, Carl

Ruetz, Doug Wilcox

IJC staff: Lizhu Wang, John Wilson

Definition

This indicator tracks the trends of Great Lakes coastal wetland ecosystem health by measuring

the composition and density of macroinvertebrates, fish, plants, amphibians, and birds. The

Great Lakes Coastal Wetlands Consortium (GLCWC) developed indices of biological integrity

(IBIs) for each of the groups in 2002 and protocols were finalized in 2008 (GLCWC, 2008). The

five sub-indicators being used in the current monitoring project are existing individual SOLEC

indicators. The continuation of this work addresses Objective 2.2 in the US EPA Strategic Plan

of fiscal year 2014-2018. Individual IBIs are derived for each of the sub-indicators which can

be used independently as a measure of Great Lakes coastal wetland ecosystem health. However,

an overall view of wetland health can be derived by considering these sub-indicators in

combination, because they function and indicate anthropogenic disturbance at different spatial

and temporal scales and have varying resolution of detection.

Indicator Relevance

This indicator is directly relevant to Annex 7–Habitat and Species since coastal wetlands provide

critical breeding and migratory habitat for wildlife such as birds, mammals, reptiles, and

amphibians. These habitats are also critical spawning and nursery areas for many fish species of

ecologic and economic importance. This indicator is indirectly relevant to the other annexes

because coastal wetlands trap, process, and remove nutrients and sediment from Great Lakes

nearshore waters; and recharge groundwater supplies. However, over half of all Great Lakes

coastal wetlands have been destroyed by human activities and many remaining coastal wetlands

suffer from anthropogenic stressors such as nutrient and sediment loading, fragmentation,

invasive species, shoreline alteration, and water level control, as documented by a bi-national

Great Lakes-wide mapping and attribution project (Albert and Simonson, 2004; Ingram and

Potter, 2004). Therefore, conservation of remaining coastal wetlands and restoration of

previously destroyed wetlands are vital components of restoring the Great Lakes ecosystem and

this indicator can be used to report progress toward such an objective.


1. Macroinvertebrates

Macroinvertebrate samples should be collected annually from the dominant plant zones in

each wetland (Uzarski et al., 2005 using dip nets in accordance with standard SOLEC

protocols. Plant zones are defined as patches of vegetation in which a particular plant type

or growth form dominates the plant community based on visual coverage estimates.

Numerous replicate samples are collected from each plant zone within each wetland.

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Sampling should begin in mid-June in the most southerly regions of the Great Lakes and

continue into early September, moving north when emergent plants generally achieve

maximum annual biomass. Macroinvertebrate abundance by taxon data is used to calculate

an IBI score in accordance with GLCWC protocols.

2. Fish

Fish should be sampled using three replicate fyke nets in each major plant zone (wet

meadow, emergent vegetation, and submergent vegetation) in each wetland for one net-

night (Uzarski et al., 2005). Sampling locations should correspond with those for

macroinvertebrate and water quality sampling. The timing of sampling should correspond

with the maturity of the vegetation in each system. Fish abundance by taxon is used to

calculate the GLCWC (2008) IBI scores.

3. Plants

Aquatic plants from each wetland is sampled from three transects perpendicular to depth

contours crossing wetland vegetation zones during July and August. The number of

vegetation zones will vary depending on each particular wetland. Operationally-defined

vegetation zones are wet meadow, emergent vegetation, and submergent vegetation. Plant

abundance by species data will be used to calculate wetland ecosystem health according to

GLCWC (2008). The score derived for ecosystem health based on plants relies heavily on

the Floristic Quality Index (FQI) and the occurrence of invasive species.

4. Amphibian (Frogs and Toads)

Amphibian occurrence in each wetland is sampled by listening and counting frog and toad

(anuran) vocalizations in accordance with SOLEC procedures. Sampling should occur

during breeding season, which is generally in early April for southern region, but should be

later in the northern regions. This measure is still in the developmental phase and it is not

known if it can eventually be used alone as an indicator of ecosystem health. It is currently

being used to indicate temporal variation in anuran communities.

5. Birds

Birds are sampled by counting the number of species and individuals in each wetland. The

bird counting points are generally the same locations used for the amphibians where both

shoreline (i.e., approximate upland/wetland interface) and interior stations should be

sampled. Wetlands should be surveyed twice per breeding season, with a minimum of 10

days between visits. One count should be in the morning and one count in the evening.

This measure is still in the developmental phase and it is unknown if it can eventually be

used alone as an indicator of ecosystem health. It is currently being used to indicate

temporal variation in bird communities.

16

6. Wetland Area and Extent

Wetland area and extent can only be assessed using remote sensing. Recurring remote

sensing assessments should be used as a means to monitor wetland loss, hydrologic

alterations, and changes to physical habitat condition. The timing of these measurements

will be restricted by the availability of data at a given water level. An attempt to develop

wetland area and extent metrics is currently underway using GLRI funds. In 2008, the

GLCWC recommended a two-tiered wetland mapping system at 30-m and 1-m resolution

be conducted every 5 years. Potential metrics may include gains and losses of wetland

area, land cover/land use adjacent to each wetland, changes in land use/land cover across

the basin, and area dominated by invasive vegetation.


1. Chemical/Physical

Basic chemical and physical data should be collected concurrently with invertebrate and

fish samples in accordance with the GLCWC Monitoring Plan (GLCWC, 2008). Water

quality is sampled from single composite samples from each vegetation zone and

associated with invertebrate and/or fish sampling. The measurements include

temperature, dissolved oxygen, pH, specific conductivity, transparency tube clarity,

oxidation-reduction potential (redox), and in situ chlorophyll fluorescence. Alkalinity,

turbidity, soluble reactive phosphorus (SRP), [nitrate+nitrite]-nitrogen, ammonium-

nitrogen, chlorophyll-a, total nitrogen (TN), total phosphorus (TP), chloride, color, and

sediment percent organic matter should be measured in the lab.

2. Overall Index of Wetland Health

While the individual indices of biological integrity (IBIs) derived for each of the

measures can be used independently to assess coastal wetland health, an overall index of

wetland health can potentially be derived by combining these individual scores and

realizing that the specific indicators represent disturbance within different portions of the

individual wetland along a hydrologic gradient, and therefore, providing the most reliable

and complete measure of the extent, composition and quality of coastal wetlands in the

basin. An attempt to combine sub-indicators into an overall measure of wetland health is

currently underway.


This indicator consists of the composition and density of macroinvertebrates, fish, plants,

amphibians, birds, and water quality measures. Currently, about 200 wetlands are sampled

annually since 2011, which is funded by GLRI through 2015 (about $2 million per year). Upon

completion of the fifth year, the coastal wetlands greater than 4 hectares with a surface water

connection to the Great Lakes will be sampled and a baseline will be established. The five

measures that comprise this indicator are existing individual SOLEC indicators. Individual IBIs

are derived for each of the measures and can be used independently as a measure of coastal

17

wetland health, based on a percentage of points possible reflected as ‘reference conditions’ to

‘extremely degraded’. However, an overall view of wetland health can be derived by

considering these sub-indicators in combination, because they function and indicate

anthropogenic disturbance at different spatial and temporal scales and have varying resolution of

detection. For example, the vegetation sub-indicator tends to indicate coarse scale regional

variation of the dryer portions of the wetland while invertebrates detect much more local

disturbance of the lakeward portion of the wetland within regions. Fish tend to detect

disturbance somewhere between the local and regional scale. The geographic scale of

disturbance for birds and amphibians is not yet determined, nor is the resolution for detecting

ecosystem health. Landscape measures are used to determine loss, transformation and

restoration of wetland types experiencing varying degrees of anthropogenic disturbance.

However, landscape measures have been challenging due to data gaps and because coastal

wetlands are extremely dynamic systems; they migrate, disappear, and appear with changing

water levels not necessarily related to anthropogenic disturbance.

3.2.3 Land Cover and Fragmentation Status

Expert workgroup members: Scott Sowa, Dave Allan, Mark Nelson, Hobie Perry, Randy

Swaty, Dave Ullrich

IJC staff: Lizhu Wang, Vic Serveiss

Definition

This indicator assesses the rate and extent of change to, and the fragmentation of, natural land

cover within the Great Lakes watersheds. This landscape scale indicator will inform inferences

about the major proximate causes of changes and trends in other biological communities,

physical habitat, and water quality indicators that are more directly reflective of the health of the

Great Lakes ecosystem.

Indicator Relevance

This indicator is relevant to GLWQA Annex 4-Nutrients that manages phosphorus and other

nutrient concentration and loading from watersheds to the lakes. It is also relevant to Annex 2-

LAMPs, Annex 7-Habitat and Species, and Annex 8-Groundwater, since the changes in this

indicator directly affect trends in other physiochemical and biological indicators that are more

directly reflective of the health of the Great Lakes ecosystem.


This indicator includes land cover conversion measures and fragmentation measures.

1. Conversion measures:

Natural land cover type unchanged (%).

Major change in natural land cover types (%).

Major change to anthropogenic non-urban or industrial land use (restorable) (%).

Major change to urban or industrial land use (“Unrestorable”) (%).

http://www.fs.fed.us/research/people/profile.php?alias=Nelson

18

Changed to water (%).

A change matrix will be developed so that each 1 km pixel in the analyses is given a “rating of

change”. For example, a change from wetland to urban would receive the most negative value

(e.g. -2), no change would receive a neutral value (e.g., 0) whereas restoration of a non-natural

type to natural habitat would receive a positive value (e.g. 2). The pixels in the analysis would

be classified this way to give a visual representation of change in addition to the tabular data.

2. Fragmentation measures:

Average number of patches for each natural land-cover class, which can be measured

using Fragstat software at 1 ha scale.

Average patch size for each natural land cover class.


1. The five land conversion and the two fragmentation measures can be potentially

aggregated into an overall index. However, the aggregation approach is yet to be

determined.

2. The Forest Spatial Integrity Index is developed for evaluation of forest fragmentation.

Forest Spatial Integrity Index is calculated based on forest patch size, spatially weighted

forest cover density, and connectivity using LANDFIRE Refreshed Existing Vegetation

Type data. Presently, the LANDFIRE data is available only for U.S. side of the Great

Lakes. It is possible to crosswalk LANDFIRE data to related Canadian ecological data

systems, but development of analogous data, while extremely valuable, would be

expensive.


As natural lands convert to agricultural or urban use, the ecosystem products and services

provided by those cover types such as timber, water storage and purification, wildlife habitat,

carbon storage, recreation, and aesthetic beauty, etc. are changed. The loss of natural habitat,

particularly forest, can also have profound economic impact on communities that rely on the

forest for food and economic development. Furthermore, conversion of natural land cover to

urban and agricultural lands leads to increased runoff and associated increased inputs of

sediments, nutrients, and contaminants to inland waters and the Great Lakes (Seilheimer et al.,

2013; Wolter et al., 2006). High rates of land conversion place stress on the natural ecosystem.

Growth in human population and resource consumption are drivers for more development, which

displace both agricultural and natural lands. Other things being constant, high conversion rates

are associated with rapid rates of development. The spatial pattern of land use conversion affects

wildlife habitat and associated wildlife populations and communities. For example,

fragmentation of natural or semi-natural lands can create migration barriers or inhospitable

habitats for wildlife and interfere with other ecological processes. Forest interior breeding birds

in the Great Lakes and other ecoregions have been shown to have higher breeding success in

relatively unfragmented landscapes than fragmented landscapes (Robinson et al., 1995). The

size and number of natural habitat patches has been shown to have a significant influence on a

19

variety of wildlife populations, including populations in the Great Lakes region (Saunders et al.,

2002). Finally, small ownership parcels found in fragmented landscapes complicate

management and cooperation at landscape and watershed scales due to the increased number of

stakeholders that must be involved in land management decisions (Pijanowski and Robinson,

2011).

*There are coarser-scale land cover and use data available for Canada, e.g., “NACP Forest Age

Maps at 1-km Resolution for Canada (2004) and the U.S.A. (2006)”

(http://daac.ornl.gov/NACP/guides/NA_Tree_Age.html)

3.2.4 Seasonal and Long-Term Fluctuations in Great Lakes

Water Levels

Expert workgroup members: Drew Gronewold, Norm Grannemann, John Allis, Glen Benoy,

Jacob Bruxer, David Fay, Mike Shantz, Al Steinman

IJC staff: Lizhu Wang, Glenn Benoy, Vic Serveiss

Definition

This indicator tracks seasonal, inter-annual, and long-term (i.e. decadal) trends in lakewide-

average water levels across each of the Great Lakes. The set of measures associated with this

indicator are calculated from existing estimates of lake-wide average water levels based on gage

measurements since 1918. This formal network of gages for each lake was established and has

served as the basis for an internationally-coordinated set of monthly-average water level

measurements. Lake-wide average water levels based on gage measurements is also available

dated back to 1860, the year in which at least one gage (“master gage”) was installed along the

shoreline of each of the Great Lakes. The measures proposed below are based on monthly

average water level records from gage data collected between 1918 and present. It is suggested

to not use the data before 1918 because of the concern that glacial isostatic adjustment may bias

the measures.

Indicator Relevance

This indicator is directly relevant to GLWQA Annex 9-Climate Change Impacts, since water

level characteristics could be strongly influenced by climate change. This indicator is also

relevant to Annex 7-Habitat and Species because water level change has strong influences on

Great Lakes habitat and biological communities associated with them. Impacts of alterations in

the water level fluctuations of the Great Lakes on shoreline ecosystems (particularly coastal

wetlands) are widely-documented, and underscore important additional (but less apparent)

relationships between ecosystem response and both human intervention (such as implementation

of outflow regulations on Lakes Superior and Ontario) and climate change (Wilcox et al., 2002;

Hartmann, 1990). In general, water level fluctuations have both direct and indirect connections

to nearly every aspect of ecosystem and coastal water quality (whether through connections to

the magnitude and timing of tributary inflows, or interrelationships between evaporation, ice

cover, water temperature, and water quality). This suite of relationships is particularly relevant

given the current period of persistent low water levels on Lakes Michigan and Huron

http://daac.ornl.gov/NACP/guides/NA_Tree_Age.html

20

(Gronewold et al., 2013), including the record low monthly average levels set on the Lake

Michigan-Huron system in December 2012 and January 2013, the record monthly lows set on

Lake Superior for the months of August and September (both in 2007), and the record monthly

high water level set in 1986 for Lake Michigan. Notably, the monthly average water level

recorded on Lake Michigan-Huron in January 2013 is the lowest monthly average water level

ever recorded for the Michigan-Huron system. These recent phenomena underscore the need for

explicit identification of water level measures that provide a suitable context within which to

assess and understand drivers behind, and implications of, observed extreme low (and high)

water levels and shifts in the natural seasonal cycle (Lenters, 2004).


This indicator includes four measures:

1. Long-term water level variability

This measure is derived by assessing trends in the “rolling” 5- and 30-year standard

deviation of monthly mean water levels over the period of record for each of the Great

Lakes. Water level variability across different time scales can serve as indices of

significant changes in regional meteorology and climate and a reflection of anthropogenic

influence (including regulation of outflows from Lakes Superior and Ontario), and an

important indicator of potential impacts on coastal ecosystems, hydropower capacity, and

other socioeconomic factors.

2. Timing of seasonal water level maximum and minimum

This measure is based on assessing changes over time in the month in which the seasonal

water level maximum and minimum occur. Water levels on each of the Great Lakes

follow a strong seasonal pattern (Lenters, 2004) in which water levels tend to rise in the

spring (as a result of increasing precipitation, melting of snow from the previous winter,

and decreasing over-lake evaporation) until a peak is reached in mid-summer. Water

levels then typically decline through the fall months (primarily through increased

evaporation rates and reduced runoff), reaching a typical seasonal low in early winter.

Persistent shifts in the timing of either the seasonal maximum or minimum may reflect

shifts in the regional water budget (including changes in the timing and magnitude of

precipitation, tributary flows, and evaporation) and provide insight into potential impacts

on aquatic plants and fish spawning habitats, and other sensitive aspects of the coastal

ecosystem.

3. Magnitude of seasonal rise and decline

This measure is based on assessing trends over time in the magnitude of spring rise, and

the magnitude of fall decline. A persistent increase in the magnitude of spring rise might,

for example, reflect increasing “flashiness” in tributary inflows, while periods of decreased

declines in the fall may reflect cooler water temperatures and diminished evaporation rates.

These regional drivers of climate have important implications for the magnitude of

seasonal rises and declines, and impacts on the coastal ecosystem. Long-term changes in

Great Lakes water levels often occur through persistent above- or below-average water

21

level changes in the spring and fall. For example, systematic increases in long-term water

levels are often a consequence of consistent above-average runoff rates in the spring and

below-average evaporation rates in the fall. In addition, the magnitude of seasonal rise and

decline (within a given year) has important implications for coastal recreational activities

and the design of coastal infrastructure. It also has implications for vegetative phenology

and sediment-water nutrient exchange.

4. Lake-to-lake water level difference

This measure is based on assessing long-term trends in the difference between the monthly

mean water level for each lake and the monthly mean water level for the downstream lake.

Differences between the water levels of each of the lakes may follow a relatively consistent

and predictable pattern; anomalies in these differences may suggest an imbalance in the

regional water budget, physical changes in the channels that connect the lakes, or the

apparent and physical impacts of glacial isostatic adjustment on recorded water levels

(International Upper Great Lakes Study, 2009).


1. Dangerously low water levels

A chart-referenced low water datum (LWD) elevation is established for each of the Great

Lakes, and indicates an elevation below which water levels are not expected to decline

frequently. The frequency with which water level depths exceed the LWD is important

because, unlike long term average water levels (which are continuously calculated as new

data become available), the LWD does not change over time. This measure is based on

assessing the number of months, within each historical calendar year, for which the water

level is below LWD.

2. Seasonal water level cycle anomalies

This measure provides information similar to seasonal measures identified above, but is

based on calculating (and assessing trends in) the difference between each monthly

average water level and the average water level for that particular month.

3. Frequency of extremes

Extreme high and low water levels can have significant impacts on the regional economy

and on ecosystem health. Tracking the frequency of these extremes can shed light into

whether or not the Great Lakes system is entering a new (or staying within a given)

hydrologic regime. This measure, then, is based on documenting years in which a

monthly (or all-time) water level maximum or minimum was recorded, and assessing the

distribution of time intervals between those extremes.

22


Maintenance and operation of the Great Lakes water level monitoring network is critical to

understanding the Great Lakes regional water budget, and is currently a central regional mission

of both the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service

(NOAA-NOS), and the Fisheries and Oceans Canada - Canadian Hydrographic Survey (CHS).

Synthesizing and communicating lakewide-average water level data is coordinated through a

regional partnership led by the United States Army Corps of Engineers (USACE) Detroit

District, and Environment Canada. Understanding changes in the proposed water level measures

should continue to leverage this unique and long-standing regional partnership.

The measures proposed provide an indication of water level trends over different time scales, and

there are dozens (if not hundreds) of important connections to regional climate trends, commerce

(such as commercial shipping and hydropower capacity), and ecosystem and human health

(Millerd, 2005). These connections are likely more clearly identified within other ecosystem

indicators (including, for example, shoreline integrity, coastal wetlands, and ice cover), and

should continue to emphasized in future iterations of this effort.

3.2.5 Tributary Physical Integrity

Expert workgroup member: Scudder Mackey

IJC staff: Lizhu Wang

Definition

This indicator includes three measures. The Hydrologic Alteration (R-B Flashiness Index)

quantifies the hydrologic responsiveness (i.e. flashiness) of a Great Lakes tributary to temporal

changes in precipitation and runoff. The Tributary Connectivity quantifies the percent of

mainstem channel length that is naturally accessible and is connected to the Great Lakes. This

measure can be calculated for a single tributary or multiple tributaries. The Tributary Sediment-

Turbidity quantifies changes in the magnitude and duration of turbidity referenced to a turbidity

threshold. When calibrated properly, turbidity may be used as a surrogate for changes in

suspended sediment load.

Indicator Relevance

This indicator is directly relevant to the GLWQA Annex 7-Habitat and Species objectives by (1)

measuring progress made in reducing river flashiness and increasing in connectivity between the

Great Lakes and their tributaries; (2) quantifying the longitudinal connectivity between the Great

Lakes and their tributaries necessary to meet the life history requirements of anadromous fish

and other aquatic species, including access to critical spawning and nursery habitats; and (3)

assessing sediment-turbidity changes in the tributaries as an important water quality parameter

that directly impacts aquatic vegetation and tributary fish and benthic communities.


1. Hydrologic Alteration (R-B Flashiness Index)

23

This measure describes the hydrologic response of a river to changes in

precipitation/runoff events. The R-B Index is calculated using USGS mean daily flows on

an annual basis (N=365) by dividing the sum of the absolute values of day-to-day changes

in mean daily flow by the total discharge over that time interval (Baker et al., 2004).

R-B Index =

N

n

n

N

n

nn

q

qq

1

1

1

The R-B Index is best used to track changing hydrologic responses of streams through time

by calculating the relative change in the R-B Index over time on a watershed-by-watershed

basis across the Great Lakes basin. These calculations should be updated every three to

five years.

2. Tributary Connectivity to Receiving Waters

Tributary Connectivity is the percent of mainstem channel length (naturally accessible) that

is connected to the Great Lakes. It can be calculated by individual watershed or by

multiple watersheds.

Tributary Connectivity for an individual watershed (

)

Lb is the distance between the Great Lakes and the first barrier on the mainstem channel;

Lm is the total length of the mainstem channel.

For multiple watersheds/tributaries, the connectivity to the Great Lakes is calculated by

summing the total length of mainstem channels without barriers and then dividing by the

total sum of mainstem channel lengths (N = total number of mainstem channels).

Tributary Connectivity for multiple watersheds =

N

n

m

N

n

b

n

n

L

L

1

1 x 100

Changes in watershed connectivity through time can be calculated using historical maps,

aerial photographs, and other data. These calculations should be updated every five years

(due to ongoing dam construction and/or removals).

3. Sediment-turbidity measure

This measure is quantified using Turbidity Exceedance Time and Turbidity Concentration

Ratio.

Turbidity Exceedance Time is the proportion of time that the turbidity threshold (T) is

exceeded during the time series (tn > T) divided by the total time within the series. For

24

example, a turbidity exceedance value of 0.50 indicates that the turbidity threshold was

exceeded 50% of the time on an annual basis (N=365).

Turbidity Exceedance Time =

N

n

n

N

n

n

t

Tt

1

1

)(

Turbidity Concentration Ratio is the magnitude of exceedance above the turbidity

threshold expressed as the ratio of the mean turbidity value that exceeds the turbidity

threshold (cn > T) divided by the turbidity threshold value. For example, a turbidity

concentration ratio of 3.6 indicates that the magnitude of exceedance is 3.6 times greater

than the turbidity threshold.

Turbidity Concentration Ratio = T

NTc

N

n

n

1

)(

Turbidity measurements may be used as a surrogate for suspended sediment load only

when calibration studies have been performed to generate relationships between

nephelometric turbidity units (NTU) and suspended sediment concentrations (mg/l) for

individual watersheds. Once calibrated, these indicators may be used to track changes and

longer-term trends in turbidity and suspended sediment loads within individual watersheds

through time.


None


Hydrologic Alteration (R-B Flashiness Index) - River flashiness is an important component of

the hydrologic regime as it reflects the frequency and rapidity of short term changes in river flow

to which aquatic ecosystems are adapted. Increasing or decreasing trends in flashiness may

result in increased stress at lake areas that are influenced by river flows and may influence

aquatic organisms that use rivers in part of their lives.

Possible range of values for the R-B Index is from 0 to 2. Typical values are from 0.05 (very

stable) to about 1.2 (very flashy). The Index integrates all flow data rather than specific

percentile data. The R-B Index is relatively stable from year to year and is a reliable indicator of

longer-term trends (Baker et al., 2004). Overall, the R-B Index is positively correlated with

increasing frequency and magnitude of storm events, and negatively correlated with baseflow

and watershed area.

It should be noted that small streams tend to be flashier than large rivers, and this is reflected in

generally higher R-B Index values for small streams. For small streams or streams with steep

gradients, the hydrologic response may be too rapid to be resolved by daily flow data. For such

systems, a version of the R-B Index based on hourly flow data can be used. However, Index

comparisons between daily and hourly flow data are generally not meaningful. It is therefore

25

critical that consideration be given to the type of flow data (daily or hourly) be used to calculate

R-B Index values when making year-to-year comparisons or watershed-to-watershed

comparisons.

Trend data would be reported on a watershed-by-watershed basis across the Great Lakes basin

every three to five years. In almost all cases, reductions in the R-B Index would be considered

desirable. Conversely, increases in the R-B Index would be considered undesirable. The

following trend categories are suggested for the R-B Index:

Excellent decreasing trend in flashiness (negative values - > 20% change in Index value)

Good decreasing trend in flashiness (negative values - < 20% change in Index value)

Neutral no trend in flashiness (zero change values)

Poor increasing trend in flashiness (positive change values)

Absolute values of the R-B Index are not indicative of either good or bad conditions, especially

if comparisons are made between watersheds of different types or sizes. However, when

considering watersheds with similar flow regimes (e.g. event, variable, stable, or super stable)

may be possible characterize a statistically appropriate range of R-B Index values by watershed

type or ecoregion (Baker et al., 2004). Additional analyses are needed to develop appropriate

criteria and measures to assess differences between absolute values of the R-B Index within

similar watershed types.

The R-B Index is easy to calculate from widely available data. For each gauged river, changes in

the R-B Index can be displayed graphically to illustrate trend or mapped geospatially to show

geographic changes in the distribution of flashiness. Streams with long flow records (20 years

plus) flowing across a diverse range of landscapes and watersheds would be desirable.

Tributary Connectivity to Receiving Waters - Values range from 0 to 100. A value of 0.0

represents a main stem channel that is not connected to the receiving water body (no

connectivity) and a value of 100 represents a main stem channel with unimpaired connectivity.

In almost all cases, increases in watershed connectivity would be considered desirable

(impediments to sea lamprey infestation are the exception). Conversely, decreases in watershed

connectivity would be considered undesirable. The following ranking categories are suggested

for the watershed connectivity indicator:

Excellent 90% to 100% (unimpaired connectivity)

Good 70% to 90%

Fair 50% to 70%

Poor Less than 50% (impaired connectivity)

Using GIS tools, tributary main stem lengths and dam locations can be easily measured. The

data are readily available for the entire Great Lakes Basin. A critical requirement will be

periodic updates and validation of the dam inventory database.

26

Sediment/Turbidity - The possible range of values for turbidity exceedance time is from 0 to 1.

Typical values will vary based on the established value of the turbidity threshold. Several States

and Provinces have identified threshold NTU limits for turbidity (10, 25, or 50 NTU) and

acceptable exceedance ranges (generally +10% of background or threshold values) (e.g. U S

EPA, 1988; Marquis, 2005; Trebitz et al., 2007). Extended periods of high turbidity (> 50 NTU

threshold) may result in increased ecosystem stress.

Using a threshold value of 50 NTU, typical turbidity exceedance time values may range from 0.3

to 0.7 depending on local hydrologic and geologic conditions. The possible range of values for

the turbidity concentration ratio range from 0 to infinity, but typically will range from 0 to 20.

Acceptable values of the turbidity concentration ratio would be 0.1 or less where acceptable

exceedance ranges are +10% of threshold levels.

Sensitivity analyses indicate that comparisons between daily and hourly turbidity data are

generally not meaningful (except perhaps for small streams). Hourly data can be used to

calculate daily means which then can be used to calculate values for the turbidity indicators.

Currently, these measures are only useful for trend comparisons within an individual watershed.

Turbidity measurements can be used as a surrogate for suspended sediment loads only if

appropriate statistical relationships between turbidity (NTU) and suspended sediment

concentrations (mg/l) are developed for individual watersheds. Additional studies will be needed

to assess the reliability of watershed-by-watershed comparisons under varying geological

conditions. These calculations should be updated every three to five years.

In almost all cases, low turbidity exceedance time values are considered to be more desirable

than high exceedance time values. Similarly, low turbidity concentration ratios are considered to

be more desirable than high concentration ratios. The following are general characterizations

that may be useful when evaluating the trends of these measures.

Excellent decreasing trend in turbidity (>20% change in duration and/or magnitude)

Good decreasing trend in turbidity (< 20% change in duration and/or magnitude)

Neutral no trend in turbidity (zero change in duration and magnitude)

Poor increasing trend in duration and magnitude

3.2.6 Water Temperature

Expert workgroup members: Norm Granneman, Eric J Anderson, Jay Austin, Ed

Rutherford, Chris Spence, Jia Wang, and Ram Yerubandi

IJC staff: Lizhu Wang, Glenn Benoy

Definition

This indicator tracks the trends in water temperature and extent of winter ice cover for each of

the five Great Lakes by measuring changes in duration and spatial extent of water temperature

and ice cover using long term data. This indicator measures the thermal properties of the Great

27

Lakes that affects the ecosystems’ function and influences water evaporation from the lakes that

affects lake’s water level.

Indicator Relevance

This indicator is relevant to the General Objectives of the GLWQA and Annex 9-Climate

Change Impacts in coordinating effort to identify, quantify, and understand, and predict climate

change impacts on the quantity of the waters of the Great Lakes. This indicator is also relevant

to the other Annexes since higher water temperatures and less ice cover may be related to more

and earlier algae blooms which damage water quality and habitat; less ice cover exposes the

shoreline to waves generated by winter storms that accelerates erosion; and higher temperatures

may also be related to the spread of some invasive species.


This indicator includes three measures:

1. Annual summer (July-September) surface average temperature for each lake.

This measure applies to all the five lakes.

2. Lake water thermal stratification date.

This measure applies to all the five lakes.

3. Fall lake water turnover date.

This measure applies only to lakes with data (currently, Lakes Superior, Michigan, Erie,

and Ontario have available data and Lake Huron does not have any data).

4. Maximum and average ice concentrations (use the definition by Assel, 2005).


1. Measures that are important for fish: dates of the first reported ice, date of the last reported

ice; and ice duration for each winter.


According to Assel (2005), the daily spatial average ice cover for each Great Lake was

calculated from daily grids. Daily grids were generated by linear interpolation of observed ice

cover grids between adjacent dates for a given winter season from the date of first ice chart to

date of last ice chart (Assel and Norton, 2001). Lake-averaged ice cover prior to date of first ice

chart and after date of last ice chart was assumed to be zero. The daily lake-averaged ice cover

on each Great Lake is used to calculate the seasonal average ice cover. The seasonal average ice

cover is the sum of the daily lake-averaged ice cover over a winter divided by 182 (the number

of days between 1 December to the following 31 May). The seasonal average ice cover is

calculated for days when the lake-averaged ice cover was greater than or equal to 5%.

The seasonal average ice cover is an index of the severity of an annual ice cycle. Ancillary ice

cycle variables calculated for each winter are the Julian dates that the first and last observed lake-

28

averaged ice cover was greater than or equal to 5% and the duration of the ice cover, that is, the

difference between dates of last and first ice.

3.3 Chemical Indicators

3.3.1 Atmospheric Deposition of Chemicals of Mutual Concern

Expert workgroup member: Todd Nettesheim

IJC staff: Jennifer Boehme, Antonette Arvai

Definition

This indicator will report on spatial patterns and temporal trends of concentration of chemicals of

mutual concern in the atmosphere and precipitation of the Great Lakes region. The indicator will

be used to infer potential impacts of toxic chemicals from atmospheric deposition loadings on the

Great Lakes aquatic ecosystem, as well as to infer the progress of various programs toward

virtual elimination of toxics from the Great Lakes.

Indicator Relevance

This indicator is relevant to the General Objective of the GLWQA that the waters of the Great

Lakes are free from pollutants in quantities or concentrations that that could be harmful to human

health, wildlife, or aquatic organisms, through direct exposure or indirect exposure through the

food chain. This indicator is also relevant to Annex 3-Chemicals of Mutual Concern of the

GLWQA, the purpose of which is to “reduce the anthropogenic release of chemicals of mutual

concern, recognizing: (i) that chemicals of mutual concern released into the air, water, land,

sediment, and biota should not result in impairment to the quality of the Waters of the Great

Lakes; and (ii) the need to manage chemicals of mutual concern including, as appropriate, by

implementing measures to achieve virtual elimination and zero discharge of these chemicals.”

The Annex 3 further calls for the Parties to (i) monitor and evaluate the progress and

effectiveness of pollution prevention and control measures; (ii) exchange, on a regular basis,

information on monitoring, surveillance…; (iii) identify and assess the occurrence, sources,

transport, and impact of chemicals of mutual concern, including spatial and temporal trends in

the atmosphere…; and (iv) identify and assess loadings … from the atmosphere.


It is proposed that the Atmospheric Deposition indicator be largely based on the well-established

SOLEC indicator Atmospheric Deposition of Toxic Chemicals (Nettesheim et al., 2014). The

atmosphere is a key source of many persistent, bioaccumulative, and toxic chemicals to the Great

Lakes and hence into Great Lakes fishes. The atmosphere was first recognized as an important

source in the 1980s and later confirmed with data from the Integrated Atmospheric Deposition

Network (IADN) and Lake Michigan Mass Balance study. Recent IADN and Mercury

Deposition Network (MDN) data and publications indicate that the atmosphere remains an

important source of PBT. Chemicals of mutual concern in the atmosphere and precipitation will

29

be measured at IADN and MDN stations, using the protocols established by the binational IADN

network and MDN respectively. Additional chemicals of mutual concern may be added as they

are selected by the GLWQA Annex 3 sub-committee.

IADN and MDN are well-established international monitoring programs with protocols for

sampling frequency, site selection, and sampling and analytical methods, with stations in the

Great Lakes region that could be utilized for this indicator. For example, IADN has established

one master station on each of the five Great Lakes: Eagle Harbor (USA) on Lake Superior,

Sleeping Bear Dunes (USA) on Lake Michigan, Burnt Island (Canada) on Lake Huron, Sturgeon

Point (USA) on Lake Erie and Pt. Petre (Canada) on Lake Ontario. Additional satellite stations

increase the resolution capability of IADN, which could be incorporated into the geographic

scope of this indicator.


None


Air (vapor and particle) samples are collected for 24 hours every 12 days. Precipitation samples

are integrated over each month. Annual average concentrations will be calculated and reported

using these measurements. Spatial and temporal trend analyses will be performed on the IADN

data using a variety of statistical tools (Venier et al., 2012; Venier and Hites, 2010a; Venier and

Hites, 2010b).

Weekly composite precipitation samples will be collected and analyzed for mercury across the

Great Lakes basin at MDN stations, using the same strict sampling and analytical protocols

established under the network. Annual mercury concentrations, precipitation depths, and wet

deposition will be calculated and reported using this data. Spatial and temporal trend analyses

will be performed on the MDN data using a variety of statistical tools (Risch et al., 2012; Prestbo

and Gay, 2009).

Air concentrations respond rapidly to changes in emissions, but it is not known how rapidly the

lakes and the fishes in them will respond (“environmental hysteresis”). This makes atmospheric

measurements a very useful tool for tracking progress as a result of management actions.

3.3.2 Chemicals of Mutual Concern in Water

Expert workgroup members: Michael Murray, Deborah Swackhamer, Gail Krantzberg, and

Conrad DeBarros, Gary Klecka

IJC staff: Jennifer Boehme

30

Definition

This indicator addresses total concentrations of selected legacy toxic chemicals and chemicals of

emerging concern in water that are determined at selected offshore and nearshore sites in each

lake on a two-to-three-year basis. The specific chemicals of mutual concern, including legacy

and emerging chemicals, will be selected by the Great Lakes Executive Committee as per Annex

3 of the GLWQA. The purpose of the indicator is to assess the magnitude and direction of trends

of chemicals of mutual concern (CMCs) in Great Lakes surface water, the potential for human or

ecological impacts, and progress toward virtual elimination of toxic substances in the Great

Lakes basin (Dove, 2011).

Indicator Relevance

An aqueous concentration indicator is directly relevant to the General Objective of the GLWQA,

specifically that the Lakes be “free from pollutants in quantities or concentrations that could be

harmful to human health, wildlife, or aquatic organisms, through direct exposure or indirect

exposure through the food chain…” The indicator is also relevant to the Article 3 Specific

Objective that substance objectives (or numeric targets) be developed “to manage the level of a

substance or combination of substances to reduce threats to human health and the environment in

the Great Lakes Basin Ecosystem.”


The indicator would be obtained through integrating data from direct measurements of aqueous

concentrations of various CMCs selected from those listed pursuant to Annex 3 of the renewed

GLWQA.

Currently, the GLWQA Annex 3 Subcommittee is forming a task team to evaluate the first list of

CMC candidates put forward by Environment Canada and the USEPA, with their reports and

recommendations on the first list of CMCs due to the Annex 3 Subcommittee by October 2014.

The first recommended CMCs and supporting documentation based on the task team reports will

then be submitted by the Annex 3 Subcommittee to the Great Lakes Executive Committee for

approval by December 2014. As part of this process, the Annex 3 Subcommittee will develop an

approach for preparing bi-national strategies for CMCs which may include research, monitoring,

surveillance and pollution prevention and control provisions.

The selected CMC concentrations should be measured from data collected every two-three years,

and at selected offshore and some nearshore sites, during the spring isothermal period. Site

selection should represent the diversity of aquatic habitats in each lake (i.e., nearshore sites at

different distances from major tributary mouths, offshore sites in different basins), building off

current efforts used through SOLEC. SOLEC Indicator 118 Toxic Chemical Concentrations in

Offshore Waters incorporates multiple chemical components including mercury and

organochlorine compounds, which could provide partial overlap with CMCs identified in the

future through the Annex 3 Subcommittee process described above. However, its focus on

offshore sampling locations restricts its geographic scope relative to the scope of sampling

locations proposed here.

31


None


For future consideration, it is recommended that managers also consider the potential additional

monitoring value of passive techniques, such as semipermeable membrane devices (for

semivolatile organic compounds, e.g. Alvarez, 2010) and the polar organic chemical integrative

sampler (POCIS) technique for more polar compounds (e.g. Li et al., 2010). Such techniques are

already in use in selected areas, and could be phased into existing monitoring programs for toxic

chemicals in the Great Lakes more broadly following a method development and evaluation

phase. Resulting data could assist in determining local and regional differences in CMCs as well

as further monitoring and management actions that might be pursued concerning CMCs in the

Lakes.

Additional factors to consider in identifying measurement parameters for the CMC indicator

include consideration of ongoing sensitivity issues (including as legacy chemical concentrations

continue to decline); spatial and temporal considerations (e.g. number and locations of sites in

nearshore vs. offshore areas, sampling frequency); changes in ancillary factors, such as food

webs and climate (e.g. Carlson et al., 2010); and issues of statistical power and trend detection

(e.g. Chang et al., 2012).

3.3.3 Contaminants in Groundwater

Expert workgroup members: Norm Granneman, Gary Bowen, Emil Frind, Dale

VanStempvoort, Al Kehew, Bill Alley

IJC staff: Antonette Arvai, Lizhu Wang

Definition

Groundwater is an important component of the hydrologic cycle and, therefore, groundwater

quality is an important factor in determining the overall quality of water in the Lakes.

Groundwater is important to ecosystems in the Great Lakes Region because it is, in effect, a

large, subsurface reservoir from which water is released slowly to provide a reliable minimum

level of water flow to streams, lakes, and wetlands. Groundwater discharge to streams generally

provides good quality water that, in turn, promotes habitat for aquatic animals and sustains

aquatic plants during periods of low precipitation. The major groundwater resources issues in

the Great Lakes Region revolve around 1) the quantity of groundwater, 2) groundwater and

surface-water interaction, 3) changes in groundwater quality as development expands, and 4)

ecosystem health in relation to quantity and quality of water. This indicator includes the quality

and quantity of the groundwater in the Great Lakes region, and its interaction with the surface

water in the Great Lakes basin.

Indicator Relevance

This indicator is relevant to the General Objective of the GLWQA in measuring progress toward

protecting the waters of the Great Lakes from the harmful impacts of contaminated groundwater.

32

This indicator is also relevant to Annex 8-Groundwater, which contributes to the achievement of

the objectives of the Agreement.


This indicator will measure physical and chemical parameters from various river watersheds

where they have direct influence on each of the 5 Great Lakes.

1. River Watersheds

The recommended rivers include those that have a good baseflow component and in

watersheds that are representative of

1) Agricultural;

2) Urban; and

3) Forest areas

Lake River Dominant Watershed Type

Lake Ontario Humber River (ON) Urban

Ganaraska River (ON) Agriculture/Rural

Duffins Creek (ON Agriculture/Rural

Genesee River (NY) Forest/Agriculture/Urban

mix

Oak Orchard Creek

(NY)

Agriculture

Eighteenmile Creek

(NY)

Agriculture

Salmon Creek (NY) Forest

Black River (NY) Forest

Lake Erie Big Creek (ON) Agriculture

Kettle Creek (ON) Agriculture

Grand River (ON) Urban

Maumee River (OH) Agriculture/some urban

Sandusky River (OH) Agriculture/some urban

Lake Huron Thunder Bay River

(MI)

Forest

Au Sable (MI) Forest

Saugeen River (ON) Agriculture

Spanish River (ON) Mining

Pine River (ON) Agriculture

Nottawasaga River

(ON)

Forest/Rural

Lake

Superior

St. Louis River (MN) Forest/Rural

Lake Manitowoc River (WI) Agriculture

33

Michigan Muskegon River (MI) Forest/Agriculture mix

2. Chemical and Physical Parameters

The parameters for measure include those that are common to all river watersheds in

addition to parameters specific to urban and agricultural watersheds.

Common to all river

watersheds

Location, water level and/or flow, temperature,

pH, TDS, nitrate, chloride, sulfate, calcium,

magnesium, sodium, potassium, carbonate,

bicarbonate

Additional Urban

Parameters

Total chlorinated compounds, BTEX (benzene,

toluene, ethylbenzene, xylenes), arsenic,

cadmium, zinc

Additional

Agriculture

Parameters

Phosphorus, triazine herbicides


None


Groundwater discharge is a long-term, persistent component that results from the part of

precipitation that infiltrates into the soil, percolates into an aquifer, and then flows to a stream,

lake, or wetland. Most groundwater/surface-water interaction in the Great Lakes basin takes

place in the near surface unconsolidated glacial-deposit aquifers. Because groundwater is so

highly distributed in the Great Lakes basin, representative locations to conduct measurements of

changes in groundwater quality that demonstrate the state of the groundwater resource as it

relates to Great Lakes issues are needed.

Measures focus on groundwater as a transmitter / vector of contaminants and nutrients to the

Great Lakes mostly as it impacts the quality of water in streams flowing into the Great Lakes. It

also impacts the ecology / habitats of streams that are interconnected with ecology of the Great

Lakes such as fish spawning and migration, wetland health, tributary physical integrity, and

water temperature.

Groundwater data will be obtained from water from selected wells and stream reaches unaffected

by waste water discharge during baseflow conditions. Groundwater data will be summarized

from existing data collected by federal, state, provincial, regional and local authorities at

locations that illustrate the effects of human-induced changes to groundwater quality from urban

and agricultural development. Some of this representative data can focus on water quality in

water from streams under baseflow conditions and other data will be for water from wells that

34

will be used in conjunction with the streamflow data. Because of the slow movement of

groundwater, the effects of surface activities on groundwater flow and quality can take years to

manifest themselves.

3.3.4 Persistent, Bioaccumulating, Toxic (PBT) in Biota

Expert workgroup members: Jeff Ridal, Michael Murray, Conrad deBarros, Gary Klecka

IJC staff: Vic Serveiss, Lizhu Wang

Definition

The persistent, bioaccumulating, toxic substances (PBTs) in biota indicator is an assessment of

the trends in the concentrations of PBTs in whole fish and fish-eating birds. It can be used to

describe temporal and spatial trends of bioavailable contaminants in representative biota

throughout the Great Lakes; to infer the impact of contaminants on the health of fish and bird

populations; to infer the effectiveness of remedial actions related to the management of critical

pollutants; and to document and describe the trends of chemicals of emerging concern.

Indicator Relevance

This indicator is relevant to the General Objectives of the GLWQA in measuring progress made

in allowing for human consumption of fish and wildlife unrestricted by concerns due to harmful

pollutants and being free from pollutants in quantities or concentrations that could be harmful to

human health, wildlife, or aquatic organisms, through direct exposure or indirect exposure

through the food chain. This indicator is also relevant to the GLWQA objectives of Annex 1-

Areas of Concern, Annex 2-Lakewide Management, Annex 3-Chemicals of Mutual Concern, and

Annex 10-Science.


This indicator will measure:

1. PBT chemicals in Great Lakes whole fish, specifically the top predators Lake Trout

(Salvelinus namaycush), Walleye (Sander vitreus) and the forage fish, Rainbow Smelt

(Osmerus mordax). Other species of forage fish could also be considered (e.g., yellow

perch, spottail shiners).

2. PBT chemicals in Great Lakes Herring Gull (Larus argentatus) eggs and in Bald Eagles.

3. The PBT chemicals to be measured include PCBs, organochlorine pesticides, dioxins and

furans, and trace metals including mercury. Additional chemicals of mutual concern with

PBT properties can be added as they are selected by the GLWQA Annex 3 Subcommittee.

Other Indicators Considered

None

35


This indicator is largely based on two well-established SOLEC indicators: (1) contaminants in

whole fish and (2) contaminants in fish-eating colonial waterbirds, as well as the newly

developed SOLEC indicator for Bald Eagles. The whole fish indicator assesses the temporal and

geographic trends in the chemical contaminant levels in Lake Trout from Lakes Ontario, Huron,

Michigan and Superior, and Walleye from Lake Erie. Environment Canada and the USEPA both

contribute data to this indicator, although different methodologies limit the statistical analyses

that can be performed (McGoldrick et al., 2014). Environment Canada also provides data on

Rainbow Smelt, a common forage species. Samples are collected and analyzed at least every

two years at 10 established sites (2 in each of the 5 Great Lakes) by a USEPA program and

annually at 12 sites established by Environment Canada in Superior, Huron, Erie and Ontario. It

is recommended that sampling be conducted at a minimum at 2 sites per lake, and at a frequency

of at least every two years. In addition, consideration should be given to including a warmwater

fish species (e.g. largemouth bass) to greater represent the whole fish community. Criteria for

selection could include significance as a food source, relevance of the species to the whole lake

community, and ease of monitoring (e.g., via existing contaminant monitoring in state and

provincial programs, assuming a similar protocol is adopted).

Through existing USEPA and Environment Canada monitoring programs, contaminant analyses

in whole fish reported include legacy PBTs such as PCBs, organochlorine pesticides, dioxins and

furans, mercury and other trace metals, and also contaminants of emerging concern such as

polybrominated diethyl ethers (PBDEs), fluorinated chemicals and synthetic musks. Trends

through time are assessed using first-order log-linear regression models of annual median

concentrations to estimate percent annual declines. Concentrations are also compared to

applicable benchmarks for concentrations in whole fish. It is recommended that this chemical

suite and trend analysis approach be continued.

Regarding the second indicator component, Herring Gull eggs are collected annually by

Environment Canada at 15 sites representative of all 5 Great Lakes. Contaminants analyzed

include PCBs, organochlorine pesticides, dioxins and furans, mercury and other trace metals, and

(since 2000) PBDEs. An archival database of sample extracts has been established and should

be maintained for retrospective analysis. In addition, it is recommended that sampling and

analysis continue on an annual basis. Concentrations of PBT chemicals should also be assessed

in Bald Eagles; such information will be collected as a component of a Bald Eagle indicator

being developed for the SOLEC program for 2014.

Several factors affect the annual concentrations of PBTs in biota. These include changing food

webs, prey availability, growth rates, and climatic variability; therefore, ancillary data is required

for detailed interpretation of the whole fish trend data. The Herring Gull and Contaminants in

Whole Fish monitoring programs have established ancillary data collections that include fish

age, length, weight, sex, and lipid content of the fish collected. Egg moisture and lipid contents,

and a gull diet index based on stable isotopes, trophic position, and diet fatty acid content are

collected for the Herring Gull egg program. Additional physiological measures are conducted on

the colonies from which the eggs are collected (Weseloh and Moore, 2014). Detailed data on

sample size, location and the complete suite of ancillary measurements can be sourced from the

36

program leads for the Contaminants in Whole Fish and Contaminants in Fish-eating Colonial

Waterbirds programs.

3.3.5 Phosphorus Loads and In-Lake Concentrations

Expert workgroup member: Joe DePinto

IJC staff: Mark Burrows, Raj Bejankiwar

Definition

This indicator tracks the trends in phosphorus loading to each of the Great Lakes, including

specification of loading to major embayments/sub-basins of the lakes. The loads of both total

phosphorus (TP) and dissolved reactive phosphorus (DRP) should be tracked from the major

watersheds of each lake. A second component of the indicator is to track the spatial and

temporal trends of TP and DRP concentrations in the nearshore and offshore areas of each lake

in response to the external loads.

Indicator Relevance

This indicator is directly relevant to the GLWQA Annex 4-Nutrients to manage phosphorus

concentrations and loadings in the Waters of the Great Lakes. Excessive phosphorus

concentrations in specific lakes or specific lake areas and excessive amount of phosphorus

loading from tributaries continue to be the primary stressor leading to excessive harmful and

nuisance algal conditions.


1. Phosphorus Loads

TP and DRP loadings should be calculated from the major tributaries of each basin using

method in Dolan and Chapra (2012). The major tributaries are those that taken together

contribute >80% of the TP load to the system of concern. Daily flow measurement by

USGS gage station with at least between 12 and 24 TP and DRP concentration

measurements annually (depending on flashiness of the tributary) with an emphasis of the

concentration sampling (~2/3 of samples) on high-flow events in late fall and spring.

2. In-lake Concentration

Continuation of the spring (pre-stratification) and summer stratification monitoring by the

Parties, but revisit the placement of stations and the depth resolution of sampling to better

capture nearshore-offshore gradients in the system and improve the accuracy of basin-wide

average concentrations of both TP and DRP.


None

37


Watershed phosphorus load control continues to be the primary management action that can be

taken to address the eutrophication and excessive amount of nuisance and harmful algae issues.

But two factors primarily impact the understanding and establishment of target phosphorus loads

necessary to achieve eutrophication-related targets in the lakes:

The relationship between the loading of phosphorus and in-lake concentrations has

greatly changed in the Great Lakes due to changes in how the lake ecosystem

processes those loads (e.g., Dreissenids and Cladophora);

The increases in the fraction of algal-available phosphorus in the external loads as a

result of various activities in the lake’s watershed (e.g., recent trends in DRP loading

in Maumee and Sandusky Rivers).

Hence, while phosphorus loads and in-lake concentrations are still a critical indicator of Great

Lakes ecological health, there is a need to change the way we measure that indicator to support

more informed phosphorus/eutrophication management decisions.

On a five-year rotating basis in association with the Great Lakes Cooperative Science and

Monitoring Initiative (CSMI), conduct an intensive, external load and lake-wide monitoring

program for both TP and DRP that would permit development of a phosphorus mass balance

model that can serve as an indicator of how each lake is processing phosphorus to develop a

quantitative understanding of the nearshore-offshore gradients and phosphorus retention

relationships that are observed in the system. This is important to better understand and manage

the nearshore eutrophication-offshore oligotrophication that seems to be resulting from

ecosystem changes in the lakes. Also, it can be inserted into the CSMI process with virtually no

additional expense in additional data collection and relatively little additional expense for model

application. A pilot study, perhaps for the data collected in Lake Huron during 2012 by making

some revisions to the existing TP model (Chapra and Dolan, 2012), could help better define the

required sampling resolution for such a program.

Monitoring programs need to account for the fact that nearshore P concentrations are highly

variable in both time and space. To get a sampling value that can be confidently interpreted in

terms of inter-annual trends for a given location will require very intense monitoring.

3.4 Biological Indicators

3.4.1 Aquatic Invasive Species: Invasion Rates and Impacts

Expert workgroup members: Bill Taylor, Gavin Christie

IJC staff: Lizhu Wang, Mark Burrows, Vic Serveiss

Definition

This indicator measures the rate of invasion and status and impact. The rate of invasion is the

number of new aquatic invasive species (AIS) arriving in the Great Lakes since the last

assessment (3 year window), a retrospective analysis to identify the likely pathway by which the

38

species arrived, and an evaluation of the longer record to quantify any trend in the rate of

invasion.

The status and impact is to measure the detrimental effects of aquatic invasive species on the

Great Lakes. It specifically excludes species that are benign or perceived to be desirable species.

Status measures the relative abundance of AIS to native species of equivalent trophic position,

while impact measures how AIS affects the other ecosystem components

Indicator Relevance

This is directly relevant to the GLWQA General Objective related to preventing impacts from

aquatic invasive species and to Annex 6 – Aquatic Invasive Species objectives. It measures the

success of management actions to reduce the rate of new species arriving in the Great Lakes;

quantifies the extent to which Great Lakes are populated by AIS; and evaluates the detrimental

impact and the success of mitigation measures.


1. Rate of Invasion - plotting cumulative numbers of invasions versus time;

Recommend using binational standardized data, such as GLANSIS (Great Lakes

Aquatic Non-Indigenous Species Information System) and identifying the subset of

those non-natives that Are invasive

This is preferably done by lake, but if it is too difficult, then do all the 5 lakes together.

2. Status and impacts - several or all the following measures can be used:

Sea Lamprey - relative lakewide abundance versus target established by the Great

Lakes Commission by lake (Lake Erie may be an exception);

Plankton – invasive zooplankton biomass relative to entire zooplankton community

biomass by lake;

Asian Carp – occurrence, abundance (number or biomass), and potentially

reproduction;

Dreissenid mussels – abundance on nearshore zone hard substrate and on offshore

zone soft bottom by lake;

Round Goby – relative abundance (biomass or number) compared to all benthic fishes

abundance in nearshore and tributaries;

Ruffe - relative abundance (biomass or number) compared to all benthic fishes

abundance in nearshore and tributaries.


1. Phragmites – relative abundance and occurrence. This measure overlaps with the Costal

Wetland Indicator.

2. Molecular methods - It may also be possible to integrate molecular methods (e.g., eDNA)

into monitoring for AIS relative abundance in the future.

39


The rate of invasion measure of this indicator depends on the timely detection of new AIS. To

support rapid response programs being planned and implemented, sites that are high risk

invasion points (harbours, marinas, city waterfronts, city parks connected to Great Lakes) should

be selected and monitored. The selection of sites and the type of monitoring to be conducted at

those sites should be based on risk assessment. A pilot program that is widely considered to be

state of the art has been implemented at Duluth (USGS, 2007; Dupré, 2011). The current state of

AIS monitoring activity in the Great Lakes was reviewed by Dupré (2011), and data on AIS are

currently maintained at the Great Lakes Aquatic Non-Indigenous Species Information System

(GLANSIS). A challenge with this measure is that invasions are low frequency, stochastic

events. Therefore, it is hard to detect signal from noise.

The status and impacts measures of this indicator will generally measure AIS relative abundance

to native species of equivalent trophic position (e.g., zooplankton, planktivorous fishes) and

measure anything that may prevent the achievement of any of the General Objectives of the

GLWQA, or that contributes to a Beneficial Use Impairment (Annex 1, GLWQA). These

measures require broad-spectrum biological sampling, including plankton sampling, benthic

sampling (nearshore and offshore), wetland sampling for plants and fauna, zooplankton

sampling, and trawling for fish. Therefore, operational definition of this indicator should build

on monitoring activities put in place for other reasons, rather than require new and redundant

sampling efforts.

3.4.2 Abundance and Distribution of Fish-Eating and Colonial

Nesting Birds

Expert workgroup members: Bill Bowerman, Latice Fuentes, Pamela Martin, Robert

Letcher, Doug Crump, Kim Fernie, Michael Gilbertson, James

Ludwig, Shane DeSolla, Jeff Ridal

IJC staff: Glenn Benoy, Lizhu Wang

Definition

This indicator measures ecological integrity using population measures that are tied to the health

of individuals, colonies, and populations of fish-eating birds at multiple geographic scales; and

links biological integrity to both chemical integrity and physical integrity, which are measurable

stressors (causes) to biological integrity (effects).

Indicator Relevance

This indicator is indirectly relevant to GLWQA Annex 3-Chemicals of Mutual Concern by

directly measuring the chemical pollution of the aquatic food-web, and the health of their

populations are directly impacted by, and reflective of, the health of the biological (fish

populations), physical (habitat quality), and chemical (pollutant) integrity of the Great Lakes

ecosystem. Fish-eating birds are at the top of the Great Lakes aquatic food web and are

40

represented here by Herring Gulls and Bald Eagles. The abundance and health of these birds and

their ability to reproduce indicates the effects of chemical, physical, and ecological stressors

within the Great Lakes ecosystem. They are distributed across all 5 Great Lakes, the connecting

channels, and the St. Lawrence River. The effects of environmental pollutants on wildlife are

clearly understood by the public, utilizing the illustration of the egg-shell thinning effects to bald

eagles.


1. Population Status

a. Nest counts of Bald Eagles, Double-crested Cormorants, Herring Gulls, other colonial

water birds (e.g. Common Tern) across the lakes at relevant temporal and spatial

scales

i. Annual: Bald Eagle, Herring Gull, Double-crested Cormorant

ii. 10-year: Other colonial water birds

b. Number of adult and number of young individuals at relevant spatial scales

i. Bald Eagle Measure: Number of nestlings produced annually along Michigan,

Wisconsin, Ohio, and New York shorelines

ii. Colonial water bird Index: Number of nestlings produced and number of

returning adults of Double-crested Cormorants, Herring Gulls, and other

species within Great Lakes sub-regions

2. Health Status

a. Reproduction—Individual level

i. Bald Eagle Productivity: (number of nestlings produced/number of occupied

nesting territories)

ii. Hatch rates for Double-crested Cormorants, Herring Gulls, and Others

b. Deformities—Tissue level

jj. In situ surveys for Bald Eagle, Double-crested Cormorants, Herring Gulls, and

Others


1. Cellular/Molecular Level

a. Immune tests for Herring Gulls.

b. Biomarkers. It may not be cost efficient at this time based on current technology, but

still considered.

2. Rate of developmental deformities - Bald Eagle, Herring Gull, Colonial waterbird.


This indicator measures biological, physical, and chemical integrities of fish eating and colonial

waterbirds. Herring gull eggs have been collected annually on all 5 lakes and connecting

41

channels since 1973 (Weseloh and Moore, 2014). The locations and sizes of colonies for all

species of colonial waterbirds are documented every 10 years along all Great Lakes and

connecting channels. Fish-eating birds are indicators in many of the AOCs, and are used for

delisting criteria. While Herring Gull eggs provide a consistent, annual trend of contaminant

trends, they fail to assess direct biological effects.

Bald Eagle population surveys have been conducted along most Great Lakes shorelines and

interior areas since 1961. These surveys continue along the US shorelines of all 5 lakes, and

along Lakes Erie and Ontario in Canada, and statewide in Michigan and New York. All Great

Lakes shoreline habitat was quantified in 1992 (Bowerman et al., 2005). Blood, feathers, eggs

and tissues are collected annually (Stromberg et al., 2007; Best and Wilke, 2009; Route et al.,

2011).

Sampling of Herring Gull eggs should occur annually at the 15 CWS locations and 5 MDEQ

locations. Colonial waterbird surveys should continue every 10 years. Bald Eagle productivity

data should continue annually in current areas. Great Lakes habitat should be assessed every 10

years.

Relationships for contaminant concentrations among species and among tissues allow us to

utilize the guild of fish-eating birds as the indicator (Weseloh and Moore 2014). Cause-effect

relationships between biological outcomes and chemical, biological, and physical stressors for

each species allow for direct comparison of health across spatial and temporal scales.

3.4.3 Lower Food Web Productivity and Health

Expert workgroup members: Bill Taylor, Jan Ciborowski, Veronique Hiriart-Baer, Ora

Johannsson, Tim Johnson, Chuck Madenjian, Euan Reavie,

Lars Rudstam, Hank Vanderploeg, Sue Watson


Definition

This indicator focuses on the efficiency with which energy is transmitted from primary producers

to different levels of consumers. The indicator mainly measures phytoplankton and zooplankton

community structures and biomasses, benthos abundance and diversity, and prey fish abundance

and diversity. These measures are selected based on their inherent importance in energy transfer

and their measurability.

Indicator Relevance

This indicator is directly relevant to GLWQA Annex 4-Nutrients to maintain trophic states with

relative algal biomass and composition consistent with a healthy aquatic ecosystem in open

waters of the Great Lakes. This indicator is indirectly relevant to Annex 6-Aquatic Invasive

Species and Annex 7-Habitat and Species. This indicator reflects the principle that pelagic

communities, on average, have approximately equal biomass in exponentially widening size

classes (Sheldon et al., 1972). Material and energy flow up this size spectrum from bacteria and

phytoplankton via zooplankton to fish with varying efficiency (Borgmann, 1987). Some of this

42

production sinks from the surface euphotic zone to nourish the benthos. It may flow efficiently,

with high productivity across the size-spectrum, or it may accumulate as algae, negatively

affecting water quality while little energy reaches top predators. The purpose of this indicator is

to measure the trophic efficiency of the food web at transferring algal production to fish.

Measure Description

This indicator includes measures of phytoplankton, zooplankton, benthos, and prey fishes. Data

for these measures need to take into account spatial coverage, including nearshore and offshore

for all measures, and hard and soft substrates for benthos. Sampling method for each measure

should be standardized at least within each lake, and if possible across lakes.

1. Phytoplankton

Total biovolume of phytoplankton (volume/volume) and taxonomic composition for spring

and late summer. Taxonomic identification should be to the best detail possible (e.g.,

species) to identify atypical or non-native taxa. Abundances of taxa (e.g., blue-green algae

or large diatom blooms) will reflect conditions relative to known historical condition within

a lake. Sampling should be standardized across all lakes.

2. Zooplankton

Crustacean biomass, including Daphnia retrocurva, D. galeata, Cyclopoida,

Limnocalanus, and other Calanoida. This should be measured in a standard fashion, such

as vertical tow from bottom-2 m or top 100 m, whichever is less, with a metered 0.5-m net

with 153-µm mesh, during August or September.

3. Mysis biomass

It should be measured once a year in a standard fashion with a coarse (0.5 or 1 mm-mesh)

1-m diameter net towed vertically from the bottom to the surface. Sampling needs to be

done at night, at least 1 hour after sunset to 1 hour before sun rise, under red light (ship’s

deck lights off). The sampling design should incorporate spatial coverage of both deep

(>120 m) and shallow (50 to 75 m) depth zones. Nighttime acoustic monitoring is showing

great promise in measuring mysid biomass and could be used in conjunction with fewer net

hauls (methods are presently being developed by Rudstam et al. (2008). Date of sampling

should coincide with time period of higher numbers of larger mysids in the population.

4. Benthos

Abundance of dreissenid mussels, Diporeia, Hexagenia, Gammarus, Chironomidae

(individuals/m2), and Oligochaete Trophic Index (EC and USEPA). Separate indices are

needed for nearshore vs. offshore and hard vs soft substrate. Soft substrate should be

sampled by ponar or petit ponar grab, and hard substrate needs to be sampled by airlift

using divers.

5. Prey fishes

Prey fish biomass per unit effort for all lakes and prey fish diversity (Shannon–Wiener

Index).

43


1. Phytoplankton composition by size class

Divide algae assemblage to greater than 30 µm and smaller than 30 µm, approximating

edible vs non-edible by grazing plankton. The expert group considered that major taxa

contained more useful information.

2. Integrated measures

It is interesting, but none of the proposed have any history and all need some development.


Phytoplankton composition is an important indicator of water quality, particularly the relative

abundance of cyanobacteria versus diatoms and flagellates. The USEPA has an active program

for phytoplankton collection and analysis in the pelagic regions of all Great Lakes in spring and

summer. While counting phytoplankton is time-consuming, limiting the number of samples that

can be processed, fluorometry also offers the promise to determine plankton composition in situ

with a probe (Ghadouani and Smith, 2005) although there may still be issues with calibration to

Great Lakes conditions (Twiss, 2011). Phytoplankton counting potentially can be restricted to

the number of samples required to calibrate the fluorometer and to investigate blooms.

Zooplankton mean size directly assesses the balance between forage fishes and zooplankton

through the well-known effect of planktivory by fishes on zooplankton size-distribution,

although it may be problematical or need recalibration for lakes with Mysis (Mills and

Schiavone, 1982). It has been used in and around the Great Lakes (Taylor and Carter, 1997).

Mysis is a key link between the pelagic and benthic systems in the offshore of the Great Lakes,

transferring nutrients and contaminants between these systems and moving energy from these

systems to both benthic and pelagic fish. Of the two large, native macroinvertebrates in the

offshore of the Great Lakes which transferred lower food web production to fish, only Mysis

remains abundant.

Preyfish are sampled using trawl surveys, although acoustic surveys are gaining in importance.

The SOLEC indicator "Preyfish Populations and Communities" has endpoints for prey fish

biomass taken from Fish Community Goals and Objectives for each lake. SOLEC indicator

"Zooplankton populations" uses mean length of zooplankton sampled with a specific net size

(153 µm) as an index of the balance between forage fish and their zooplankton food.

In the Cooperative Science Monitoring Initiative intensive field years, plankton and benthos

samples should be collected from at least 5 offshore stations with long-term records, monthly

from May through October. This level of sampling intensity is also recommended for lakes of

current concern; Erie and Huron. Otherwise, multiple offshore stations should be sampled at

least three times per year.

44

3.4.4 Fish Species of Interest

Expert workgroup members: Gavin Christie, Roger Knight, James Boase, Chuck Bronte,

Mark Ebener, Jixiang He, Kevin

Kayle, Jana Lantry, Charles

Madenjian, Tom Pratt


Definition

This indicator measures status and trends in population abundance and recruitment for several

key fish species that are representative of healthy fish communities in major habitats of the Great

Lakes. It includes species that support valuable fisheries in the Great Lakes and that reflect

ecosystem health through their roles in the aquatic food web.

Indicator Relevance

The indicator is directly relevant to the GLWQA Annex 7 – Habitat and Species and is indirectly

relevant to the GLWQA General Objectives to support healthy and productive wetlands and

other habitats to sustain resilient populations of native species. This indicator is also relevant to

the other objectives that affect the food web and ultimately fishes, including being free from

pollutants in quantities or concentrations that could be harmful to aquatic organisms, through

direct exposure or indirect exposure through the food chain; being free from the introduction and

spread of aquatic invasive species that adversely impact the quality of the waters of the Great

Lakes.

Measure Description

This indicator consists of standardized scoring of lake-specific adult abundance and recruitment

for several fish species that represent various thermal and spatial habitats:

1. Cold water, off shore - Lake Trout and Lake Whitefish.

2. Cool water, near shore – Walleye.

3. Cool water, near shore, rivers, and connecting channels - Lake Sturgeon.

4. Warm water, near shore – Northern Pike and/or Smallmouth Bass/Largemouth Bass.

Data availability (quantity and quality) may limit complete spatial coverage of each lake and

may only reflect area ranges of defined fish stocks in each lake. Information from a specific area

representing ideal habitats for the species in that lake is considered appropriate for the purpose of

this indicator.

The standard scoring of each fish species at each lake/location should be developed by fisheries

experts in the inter-jurisdictional Lake Technical Committees of the Great Lakes Fishery

45

Commission. The following hierarchy of data sources will be used for calculating adult

abundance and recruitment scores:

1. Model-generated estimates of abundance at age for defined fish stocks under inter-

jurisdictional fisheries management.

2. Catch per unit effort from fishery-independent survey gears.

3. Catch per unit effort from commercial and angler fisheries.


None


A number of fish species are selected as indicator species because they belong to different

communities occupying different habitats within the lakes, which are affected by different

stresses. The “oligotrophic” fish community is associated with cold, clear, less productive, off

shore waters. The “mesotrophic” cool-water fish community is associated with more productive

waters in nearshore areas. And the “eutrophic” warm-water fish community is found in the most

productive nearshore and embayment areas of the lakes. These three broad communities are

found to varying degrees in all five of the Great Lakes with Lake Superior dominated by

oligotrophic habitat and Lake Erie mostly mesotrophic habitat. The selected fish species

represent the fish communities in each of these different ecosystems.

Native fish species are selected as indicators because they represent the original fish

communities in the different habitats, they have value to the ecosystem and to fisheries, and they

are the focus of fisheries management and restoration efforts. Being co-evolved with the rest of

the fish community and the natural ecosystem of the Great Lakes, these native represent the

natural biodiversity of the lakes. Many are of high economic value and have been affected by

fishing, often to the point of extirpation. They have been subjected to the full slate of other

environmental effects resulted from human disruption of the Great Lakes including habitat loss,

nutrient pollution, and persistent toxic pollutants. These species are the focus of active fisheries

management and of restoration efforts. While restoration efforts like stocking can complicate

interpretation of their status, the successes of these species are indicative of progress toward the

goals of the GLWQA.

Native species of interest selected include top predators and large benthivores (fish feeding on

benthic organisms). The Lake Trout is the native top predator in deeper, open waters of all of the

Great Lakes. The Lake Whitefish is the top benthivore of those same waters. The Walleye is the

top predator in the cool near-shore waters of all the Great Lakes. The iconic Lake Sturgeon is

the longest lived and largest of all Great Lake fishes, and an indicator of the connectivity of

tributaries. The Lake Sturgeon inhabits near shore and river habitats in all the Great Lakes,

connecting channels, and St. Lawrence River. Lake trout, sturgeon, and walleye are SOLEC

indicators (Bronte et al., 2014; Elliott, 2014; Kayle, 2009). The Northern Pike and basses are top

predators in near-shore waters and embayments.

46

3.4.5 Harmful and Nuisance Algae

Expert workgroup members: Sue Watson, Greg Boyer

IJC staff: Glenn Benoy, Lizhu Wang

Definition

Harmful algae or harmful algal blooms refer to blooms that are documented to contain toxins or

are composed of species with the genetic potential to produce toxins that affect human health,

livestock, pets, and other organisms. In the Great Lakes and most other freshwaters, harmful

algae toxins are exclusively produced by certain species of cyanobacteria which may not always

express their toxin genes to the fullest extent. Nuisance algae or nuisance algal blooms refer to a

broader subset of algae and cyanobacteria species that form blooms which are nontoxic to

humans but cause ecological and socioeconomic harm. Collectively, they are referred to as

harmful and nuisance algae (HNA). Excessive algal blooms refer to those blooms where

information on their composition and ecosystem effects is generally lacking. Most commonly,

this will encompass bloom events detected by remote sensing where identification of the

cyanobacterial taxa, toxicity, or ecosystem effects has not been confirmed by ground based

measurements.

Indicator Relevance

This indicator is directly relevant to the GLWQA General Objectives in measuring whether the

Great Lakes water is drinkable, swimmable, and fishable. HNA blooms are one of the most

visible indicators of impaired water quality and receive widespread attention at all levels of

society. This indicator also is relevant to most of the listed Area of Concern Beneficial Use

Impairments. HNA blooms are a result of and exacerbation of impaired water quality. Because

HNA responds rapidly to changes in nutrients and environmental stressors, this indicator can

track long and short-term management actions towards nutrient reduction and improvement of

other environmental factors.

Measure Description

This indicator consists of three measures and each measure can yield one of the three ratings:

1=good;

2=moderate; and

3=severe.

The overall lake indicator score is determined by the maximum score of any of the three

measures.

47

1. Harmful Algal Blooms (adapted from Watson and Boyer 2014)

Severe The occurrence of one or more observations has Microcystin-LR

concentrations > 10ug/L (pelagic) or >300 ug/gram dry weight (benthic)

OR

The occurrence of one or more observations have chlorophyll-a > 30 ug/L

for pelagic samples or >50% coverage for benthic samples, and dominance

(> ~80%) of the biota by potentially toxic (Microcystis, Anabaena,

Planktothrix, Oscillatoria, Lyngbya) cyanobacterial species.

Moderate Toxicity or cyanobacterial abundance is observed, but the magnitude of the

harmful algal bloom does not reach the threshold necessary to rate as

“Severe”.

Good Lakes do not display any significant cyanobacteria dominated blooms or

Microcystin-LR concentrations < 1 ug/L or <30 ug per gram dry weight.

2. Nuisance Algal Bloom

Severe The occurrence of chlorophyll-a > 30 ug/L and levels of common algal

odour compounds (e.g., geosmin, 2-MIB, b-cyclocitral, decadienal ) are

greater than human odour threshold concentrations (Watson, 2003) or

malodour or taste unacceptable to sensory screening (sniff tests or

standardized Flavour Profile Analysis; e.g. Dietrich, 2004).

OR

The occurrence of a significant number of beach posting or closure is due to

excess algal material.

Moderate Significant nuisance algal abundance is observed, but the magnitude of the

nuisance algal bloom does not reach the threshold necessary to rate as

“Severe”.

Good Lakes do not display any significant nuisance algal blooms that may impair

ecosystem functions.

3. Excessive Algal Abundance

Severe The occurrence of high levels of % coverage of nearshore (up to 15m depth)

of nuisance algae at high risk sites and reference sites, sampled from

quadrants; or % coastline with > 50% coverage or 50g dwt/m2 (Auer et al.,

2010).

OR

The occurrence of an extensive pelagic bloom as measured by timing,

intensity (average chlorophyll-a concentration), duration, aerial extent (e.g.,

Binding et al., 2011) using remote sensing techniques.

Moderate Significant excessive algal abundance is observed, but the magnitude of the

event does not reach the threshold necessary to be “Severe”.

Good Lakes do not display any significant excessive algal abundance events based

on proxy measurements.

48


None


The harmful algae and nuisance algae measures can use data from biweekly samples (or more

frequently during high risk periods if feasible) taken at high risk and reference monitoring sites

from discreet surface (0.5-1m) samples, or euphotic zone integrated samples, and/or benthic mats

from June-November. The sampling period should be adapted to local conditions and previous

records of harmful and nuisance algae seasonality, and may include winter (under ice) sampling

if warranted. This indicator also includes a third category excessive algal abundance that

includes blooms detected by remote sensing where ground or water based measurements are not

available to evaluate their toxicity or ecosystem effects.

Cost effective and feasible measures ensure long-term continuity of monitoring program to

evaluate trends and stochasticity. Differences in sampling regimes and analytical protocols

affect data compatibility and the resolution of long term trends, and sampling regimes can miss

spatial and temporal peaks. Most focus is on shoreline mats of attached algae or surface scums

of buoyancy-regulating cyanobacteria. These can appear/disappear rapidly with changes in

mixing, currents, and wind, and can produce significant spatial/temporal variance in biomass and

toxins which is difficult to sample, quantify or predict and is ‘smoothed out’ by seasonal means.

Beach and shoreline sampling requires multiple sites to capture this variance in risk and

impairment.

Chapter 4: ECOSYSTEM INDICATOR

RELEVANCE TO THE AGREEMENT OBJECTIVES AND A COMPARISON WITH

SOLEC INDICATORS

4.1 Ecosystem Indicator Relevance to the Agreement

Objectives

A key objective for this project was to make recommendations related to the adoption and

monitoring of a set of ecosystem indicators that are considered to be the key indicators in

assessing governments’ progress in achieving the General and Specific Objectives of the

Agreement. Therefore, the objectives of the Agreement have been a guiding principle in the

process of indicator nomination, selection, and definition.

49

The following table provides a general comparison regarding the alignment of the measurements

of the ecosystem indicators and the objectives of the Agreement.

COMPARISON OF GLWQA OBJECTIVES AND COMMISSION ECOSYSTEM INDICATORS

GLWQA General Objectives Ecosystem Indicator Alignment Check

(i) be a source of safe, high-quality drinking water; *

(ii) allow for swimming and other recreational use,

unrestricted by environmental quality concerns;

*

Harmful and Nuisance Algae

(iii) allow for human consumption of fish and wildlife

unrestricted by concerns due to harmful pollutants;

PBTs in predators fish (walleye and lake trout)

PBTs in prey fishes (Rainbow Smelt, yellow

perch)

PBTs in herring gull eggs

PBTs in bald eagles

(iv) be free from pollutants in quantities or

concentrations that could be harmful to human health,

wildlife, or aquatic organisms, through direct exposure

or indirect exposure through the food chain;

Chemicals of Mutual Concern in Water

PBTs in predators fish (walleye and lake trout)

PBTs in prey fishes (Rainbow Smelt, yellow

perch)


PBTs in bald eagles

Atmospheric Deposition

v) support healthy and productive wetlands and other

habitats to sustain resilient populations of native species;

Coastal Wetland Macroinvertebrate

Abundance

Coastal Wetland Amphibians Occurrence

Coastal Wetland Plants Health Index

Coastal Wetland Fish Index

Coastal Wetland Bird Abundance

Composition/quality of wetlands

Coastal Habitat Index

Land Cover and Fragmentation

Tributary Physical Integrity

(vi) be free from nutrients that directly or indirectly enter

the water as a result of human activity, in amounts that

promote growth of algae and cyanobacteria that interfere

with aquatic ecosystem health, or human use of the

ecosystem;

Harmful and Nuisance Algae

Nutrient concentrations and loadings

(vii) be free from the introduction and spread of aquatic

invasive species and free from the introduction and

spread of terrestrial invasive species that adversely

impact the quality of the Waters of the Great Lakes;

Status and Impact Aquatic Invasive Species

(abundance and distribution)

Rate of Invasion of Aquatic Invasive Species

(viii) be free from the harmful impact of contaminated

groundwater;

Contaminants in Groundwater

50

(ix) be free from other substances, materials or

conditions that may negatively impact the chemical,

physical or biological integrity of the Waters of the Great

Lakes;

Chemicals of Mutual Concern in Water

Water Level

Ice Cover

Surface Water Temperature

Fish Species of Interest

Abundance of Fish Eating and Colonial

Nesting Birds

ANNEXES ALIGNMENT CHECK

1. Areas of Concern Many indicators listed in the table apply to

this objective

2. Lakewide Management Many indicators listed in the table apply to

this objective

3. Chemicals of Mutual Concern Chemicals of Mutual Concern in Water

PBTs in predators fish (walleye and lake

trout)

PBTs in prey fishes (Rainbow Smelt,

yellow perch)


PBTs in bald eagles

Atmospheric Deposition

4. Nutrients Nutrient concentrations and loadings

5. Discharges from Vessels Status and Impact Aquatic Invasive

Species

Rate of Invasion of Aquatic Nuisance

Species

6. Aquatic Invasive Species Status and Impact Aquatic Invasive

Species

Rate of Invasion of Aquatic Nuisance

Species

7. Habitat and Species Abundance of Fish Eating and Colonial

Nesting Birds

Coastal Habitat Index

Fish Species of Interest

Land Cover and Fragmentation

Lower Food Web Productivity and Health

Tributary Physical Integrity

Composition/quality of wetlands

8. Groundwater Contaminants in Groundwater

9. Climate Change Impacts Water Level

Surface Water Temperature

Ice Cover

10. Science

D. Ecosystem Indicators Addressed by all ecosystem indicators

listed above

51

Note: * indicates gaps in the coverage of the Commission indicator set

This comparison indicates that almost all the progresses toward achieving the objectives of the

Agreement can be measured generally using the ecosystem indicators developed by the

Commission. Two gaps in the coverage relate to the objectives of drinkability and

swimmability. Indicators for the assessment of progress relative to these objectives are being

explored through a project aimed at identifying indicators related to human health, also under the

Assessment of Progress priority. Human health indicators may also be relevant to other

objectives and annexes, most notably the objective of fishability (Objective iii). An ultimate aim

of the priority is to achieve a good coverage of the Agreement objectives through compilation of

the indicators generated through the ecosystems indicator project and the human health indicator

project. A third project on program effectiveness indicators also been launched by the

Commission to understand the potential contribution of this type of indicator in assessing

progress under the Agreement.

4.2 Comparison of Commission Ecosystem Indicators and SOLEC Indicators

While the Commission was working on its indicator descriptions, the governments were working

on revising their draft 2011 State of the Lakes Ecosystem Conference (SOLEC) reports. In

September 2013, SOLEC released a State of the Great Lakes Highlights report and in March

2014, SOLEC released its final 2011 technical report. This section provides a comparison

between the ecosystem indicators recommended by the Commission in this report and the

indicators used in the 2011 SOLEC reports.

The IJC’s ecosystem indicators work selected 16 indicators to measure progress towards

GLWQA ecosystem objectives. Each indicator consists of 1-6 measures and all the 16 indicators

together have 41 measures. The SOLEC 2011 Highlights report presented 17 ecosystem

indicators. The SOLEC 2011 full report used 46 ecosystem indicators along with other

indicators related to programs, energy use, and drinking water. The table below indicates where

SOLEC indicators are similar in definition to the Commission ecosystem indicators. For

example, in Indicator #16, the two SOLEC measures, Contaminants in Whole Fish and

Contaminants in Water Birds are identical to the IJC measures for the PBTs in Biota indicator.

Some other IJC indicators, such as #3 Land Cover and Fragmentation Status, use different

measures than the SOLEC indicators.

52

IJC Ecosystem Indicators

and Measures

Indicators in 2011 SOLEC Report

1. Coastal Habitat – Shoreline Alteration Index

1) Physical shoreline indicator + Biological

shoreline indicator*

1. Hardened Shorelines*

2. Extent, Composition, and Quality of Coastal

Wetlands

2) Macroinvertebrates

3) Fish

4) Plants

5) Amphibian (Frogs and Toads)

6) Birds

7) Wetland Area and Extent*

2. Wetland Amphibians

3. Wetland Birds

4. Wetland Fish

5. Wetland Invertebrates

6. Wetland Plants

7. Wetland Extent and Composition*

3. Land Cover and Fragmentation Status*

8) Conversion measures* 9) Fragmentation measures*

8. Land Cover*

4. Seasonal and Long-Term Fluctuations in Great

Lakes Water Levels

10) Long-term water level variability*

11) Timing of seasonal water level maximum

and minimum*

12) Magnitude of seasonal rise and decline*

13) Lake-to-lake water level difference*

9. Water Levels (deviation from long term

mean)*

5. Tributary Physical Integrity

14) Hydrologic Alteration (R-B Flashiness

Index)

15) Tributary Connectivity to Receiving

Waters

16) Sediment-turbidity measure*

10. Tributary Flashiness

11. Aquatic Habitat Connectivity

6. Water Temperature

17) Annual summer (July-September) surface

average temperature*

18) Lake water thermal stratification date

19) Fall lake water turnover date*

20) Maximum and average ice concentrations

12. Surface Water Temperature (date of the

onset summer stratification)*

13. Ice Duration

7. Atmospheric Deposition of Chemicals of

Mutual Concern

21) SOLEC indicator Atmospheric Deposition

of Toxic Chemicals

14. Atmospheric Deposition

53

8. Chemicals of Mutual Concern in Water

22) Annex 3 subcommittee recommendation

15. Toxic Chemicals in Offshore Waters

9. Contaminants in Groundwater

23) Urban, agriculture, and industrial

contaminants*

10. Persistent, Bioaccumulating, Toxic (PBT) in

Biota

24) PBT chemicals in whole fishes 25) PBT chemicals in Herring Gull eggs and

in Bald Eagles

16. Contaminants in Whole Fish

17. Contaminants in Waterbirds

11. Phosphorus Loads and In-Lake Concentrations

26) Phosphorus Loads of TP and DRP* 27) In-lake concentrations of TP and DRP

18. Nutrients in Lakes*

19. TP concentration of offshore*

12. Aquatic Invasive Species: Invasion Rates and

Impacts

28) Rate of Invasion* 29) Status and impacts*

20. Aquatic Non-Native Species*

21. Sea Lamprey*

22. Dreissenid Mussels*

13. Abundance and Distribution of Fish-Eating

and Colonial Nesting Birds

30) Population Status*

31) Health Status*

14. Lower Food Web Productivity and Health

32) Phytoplankton 33) ZooplanktonMysis biomass* 34) Benthos* 35) Prey fishes*

23. Diporeia*

24. Zooplankton biomass*

25. Preyfish biomass-9 species*

15. Fish Species of Interest

37) Adult abundance 38) Recruitment*

26. Lake Sturgeon abundance*

27. Lake Trout abundance*

28. Walleye abundance*

16. Harmful and Nuisance Algae

39) Harmful Algal Blooms

40) Nuisance Algal Bloom*

41) Excessive Algal Abundance*

29. Harmful Algal Blooms offshore*

30. Harmful Algal Blooms nearshore*

54

Note: 1. Shaded boxes indicate matches between IJC and SOLEC indicators

2. SOLEC indicators listed in bold text are indicators used in SOLEC Highlight Report

3. * indicates that the indicator has a different definition than the corresponding indicator

in the other column.

Overall, two of the IJC indicators are not covered at all by the SOLEC indicator suite. Three of

the Commission indicators have almost exact matches in the SOLEC suite (shown as shaded

boxes), and the other 11 IJC indicators are similar to SOLEC indicators but are not exact

matches. Twenty three out of the 41 measures of IJC indicators are defined differently from

SOLEC indicators.

The Commission does not have the mandate or capacity to collect data for the proposed

indicators across the Great Lakes. The table indicates where work would be needed by the

governments to refine or augment the current SOLEC indicator set, and associated monitoring

and data collection activities, if these recommended indicators are to be operationalized.

31. Benthos as trophic indicator

32. Forest land in tributary buffer

33. Forest land in watershed 34. Air temperature

35. Baseflow due to groundwater discharge

36. Botulism outbreaks

37. Cladophora

38. Contaminants in sediment cores

39. Extreme precipitation events

40. Human population

41. Inland water quality index

42. Phytoplankton

43. Terrestrial non-native species

44. Water chemistry (conductivity. pH,

chloride, alkalinity, turbidity, etc.)

45. Water clarity

46. Watershed stressor index

55

Chapter 5: DISCUSSION AND

RECOMMENDATIONS

5.1 The Ecosystem Indicators

This ecosystem indicator work was undertaken as a first step toward ensuring that the

Commission is well placed to fulfill its mandate under the Great Lakes Water Quality Agreement

to report to the Parties and to the State and Provincial Governments concerning progress toward

the achievement of the General and Specific Objectives, including, as appropriate, matters

related to Annexes to the Agreement. It is the Commission’s belief that an assessment of

progress under the Agreement should include the measurement and reporting of quantifiable

indicators related to Agreement objectives. As such, this report has set out key ecosystem

indicators that the Commission sees as being vital to that mission. The report on each indicator

includes the definition of the indicator, the relevance of the indicator to the Great Lakes Water

Quality Agreement and description of its constituent measures and notes on its interpretation.

For these indicators to be operational, they must be adopted by the governments, appropriate data

must be collected through monitoring and findings must be reported to the Commission and the

general public.

The Commission recommends:

‖ The governments of Canada and the United States review the indicators with respect to

how easily they can be fully implemented and provide feedback to the Commission

regarding their potential for operationalization, in the near term or over a longer time

frame.

‖ The governments of Canada and the United States consider adopting the proposed

indicators and prioritise them for the necessary monitoring and for inclusion in SOLEC

reporting.

5.2 State of the Great Lakes 2011 reporting by SOLEC

The State of the Great Lakes 2011 Highlights Report released through SOLEC in 2013 reflects a

number of positive changes that have addressed many of the recommendations made regarding

SOLEC in the Commission’s 16th

Biennial Report. For instance, as recommended by the

Commission, the SOLEC Highlights report now uses a small set (17) of core indicators to

characterize the physical, chemical, and biological integrity of the lakes and an additional 3

indicators to measure how the ecosystem affects human health.

56

Another SOLEC accomplishment is telling the stories that answer key questions such as “What

problems are invasives causing” and “Why are there fewer sports fish”. The story telling

approach used in the technical report (released in 2014) is an outstanding way to integrate the

complex and integrated scientific indicators into descriptions that the general public can

understand. The Commission recognizes the technical complexity of the Great Lakes ecosystem

and the interconnectivity of many abiotic and biotic factors. Therefore, the scientific write-ups

in the larger 500+ page technical report and associated peer reviewed science are necessary to

support and justify the stories that are told. The Commission also applauds the lake by lake story

telling that is the final part of the Highlights report. This detailed binational data collection and

reporting provides vital input for the work of the Commission and the work of individuals and

organizations across the basin that relates to specific technical aspects of the State of the Lakes.

As its next steps on indicators under this priority, the Commission will be looking more closely

at the SOLEC reports and aiming to develop its work in a way that complements or enhances

SOLEC work and avoids duplicating efforts.

The Commission has been very appreciative of the constructive engagement of SOLEC

representatives in the Commission’s work on indicators to date.

The Commission recommends that:

‖ The governments continue to collaborate with the Commission to improve effectiveness

and reduce redundancy between the Commission’s independent binational assessment

and the government’s State of the Lake (SOLEC) report.

5.3 Next Steps for the Commission

A primary aim of the Assessment of Progress priority is to identify a small set of apex indicators

to clearly and concisely report on the progress of the parties in their implementation of the

Agreement. The ecosystem indicator project has been very useful in identifying and defining

key ecosystem indicators needed to assess progress. However when combined with the other

projects under this priority, including projects to identify human health and program

effectiveness indicators, the Assessment of Progress Priority has become an effort that is more

comprehensive than concise. As a next step, the Commission is considering how to use the

ecosystem indicators for reporting on progress, raising awareness and encouraging action – the

tasks key to the Commission’s responsibilities under the Agreement. To further this effort, the

Commission is considering forming an apex set of indicators to focus Commission assessment

and reporting activities and for communication with the public. As the Commission continues

this work, it will value the requested feedback from the governments regarding indicator

operationalization and continued collaboration with the SOLEC process.

5.4 Reporting on the Assessment of Progress Priority

57

The Commission intends to issue its final report for the Assessment of Progress Priority in 2015

for comment prior to finalization. The final Assessment of Progress Priority report will bring

together work from all projects being conducted on this priority, including the results of the

“next steps” for the Commission on ecosystem indicators, as outlined above.

58

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Great Lakes Commission, Ann Arbor, MI.

Alvarez, D.A., 2010, Guidelines for the use of the semi-permeable membrane device (SPMD)

and the polar organic chemical integrative sampler (POCIS) in environmental monitoring

studies: U.S. Geological Survey, Techniques and Methods 1–D4, 28 p., available from

http://pubs.usgs.gov/tm/tm1d4/pdf/tm1d4.pdf

Assel, R. and D.C. Norton, 2001: Visualization of Great Lakes ice cycles. Ecosystem

Transactions American Geophysical Union 82: 83.

Assel, R. 2005. Classification of Annual Great Lakes Ice Cycles: Winters of 1973–2002.

Journal Of Climate 18: 4895-4905.

Auer, M.T., L.M. Tomlinson, S.N. Higgins, S.Y. Malkin, E.T. Howell, H.A. Bootsma. 2010.

Great Lakes Cladophora in the 21st century: same algae – different ecosystem. Journal of Great

Lakes Research 36: 248–255.

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